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• The Neurobiology of Anxiety Disorders: Brain Imaging, Genetics, and Psychoneuroendocrinology
  openalex Elizabeth I. Martin, Kerry J. Ressler, Elisabeth B. Binder, Charles B. Nemeroff 2009-08-29 置信度 0.72 AnxietyMood disordersPsychologyPsychiatryDepression (economics)
• Hybrid intelligent techniques for MRI brain images classification
  openalex El‐Sayed A. El‐Dahshan, Tamer Hosny, Abdel-Badeeh M. Salem 2009-07-10 置信度 0.72 Pattern recognition (psychology)Artificial intelligenceComputer sciencePrincipal component analysisClassifier (UML)
• Abnormal processing of visual motion in dyslexia revealed by functional brain imaging
  openalex Guinevere F. Eden, John W. VanMeter, Judith M. Rumsey, José M. Maisog 等 1996-07-01 置信度 0.72 Parvocellular cellDyslexiaNeuroscienceExtrastriate cortexLateral geniculate nucleus
• An expanded set of genome-wide association studies of brain imaging phenotypes in UK Biobank
  openalex Stephen M. Smith, Gwenaëlle Douaud, Winfield Chen, Taylor Hanayik 等 2021-04-19 置信度 0.72 BiobankNeurosciencePhenotypeNeuroimagingAssociation (psychology)
• Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images
  Among brain tumors, gliomas are the most common and aggressive, leading to a very short life expectancy in their highest grade. Thus, treatment planning is a key stage to improve the quality of life of oncological patients. Magnetic resonance imaging (MRI) is …
  openalex Sérgio Pereira, Adriano Pinto, Victor Alves, Carlos A. Silva 2016-03-04 置信度 0.72 SegmentationComputer scienceArtificial intelligenceConvolutional neural networkPattern recognition (psychology)
• Brain imaging in the assessment for epilepsy surgery
  openalex John S. Duncan, Gavin P. Winston, Matthias J. Koepp, Sébastien Ourselin 2016-02-25 置信度 0.72 Epilepsy surgeryEpilepsyDiffusion MRITractographyFunctional imaging
• Very Slow Activity Fluctuations in Monkey Visual Cortex: Implications for Functional Brain Imaging
  We examined fluctuations in band-limited power (BLP) of local field potential (LFP) signals recorded from multiple electrodes in visual cortex of the monkey during different behavioral states. We asked whether such signals demonstrated coherent fluctuations ov…
  openalex David A. Leopold 2003-03-11 置信度 0.72 Local field potentialCoherence (philosophical gambling strategy)NeurosciencePhysicsVisual cortex
• Neuroimaging in traumatic brain imaging
  openalex Bruce Lee, Andrew B. Newberg 2005-03-15 置信度 0.72 NeuroimagingTraumatic brain injuryNeurosurgeryMedicineNeurology
• Functional Brain Imaging
  openalex 2013-01-01 置信度 0.72 Functional Brain ImagingNeuroimagingNeurosciencePsychologyComputer science
• A hybrid method for MRI brain image classification
  openalex Yudong Zhang, Zhengchao Dong, Lenan Wu, Shuihua Wang‎ 2011-02-13 置信度 0.72 Artificial intelligencePattern recognition (psychology)Computer scienceArtificial neural networkImage (mathematics)
• Optical brain imaging in vivo: techniques and applications from animal to man
  Optical brain imaging has seen 30 years of intense development, and has grown into a rich and diverse field. In-vivo imaging using light provides unprecedented sensitivity to functional changes through intrinsic contrast, and is rapidly exploiting the growing …
  openalex Elizabeth M. C. Hillman 2007-01-01 置信度 0.72 NeuroimagingOptical imagingMultispectral imagePreclinical imagingNeuroscience
• Structural Brain Imaging Evidence for Multiple Pathological Processes at Different Stages of Brain Development in Schizophrenia
  The underlying neurobiology of emerging psychotic disorders is not well understood. While there is evidence from structural imaging and other studies supporting the popular notion that schizophrenia arises as a consequence of an "early neurodevelopmental" lesi…
  openalex Christos Pantelis 2005-07-15 置信度 0.72 Schizophrenia (object-oriented programming)NeuroimagingPathologicalNeurosciencePsychology
• EANM procedure guidelines for PET brain imaging using [18F]FDG, version 2
  openalex Andrea Varrone, S. Asenbaum, Thierry Vander Borght, Jan Booij 等 2009-10-16 置信度 0.72 NeuroimagingMedical physicsMedicineContext (archaeology)Clinical Practice
• Fear extinction in rats: Implications for human brain imaging and anxiety disorders
  openalex Mohammed R. Milad, Scott L. Rauch, Roger K. Pitman, Gregory J. Quirk 2006-02-14 置信度 0.72 Extinction (optical mineralogy)PsychologyNeurosciencePrefrontal cortexFear conditioning
• Genetic influences on human brain structure: A review of brain imaging studies in twins
  Twin studies suggest that variation in human brain volume is genetically influenced. The genes involved in human brain volume variation are still largely unknown, but several candidate genes have been suggested. An overview of structural Magnetic Resonance (br…
  openalex Jiska S. Peper, Rachel M. Brouwer, Dorret I. Boomsma, René S. Kahn 等 2007-04-05 置信度 0.72 Brain sizeWhite matterHuman brainParahippocampal gyrusNeuroscience
• Harmonization of large MRI datasets for the analysis of brain imaging patterns throughout the lifespan
  As medical imaging enters its information era and presents rapidly increasing needs for big data analytics, robust pooling and harmonization of imaging data across diverse cohorts with varying acquisition protocols have become critical. We describe a comprehen…
  openalex Raymond Pomponio, Güray Erus, Mohamad Habes, Jimit Doshi 等 2019-12-09 置信度 0.72 NeuroimagingHarmonizationData scienceComputer sciencePooling
• A review of atlas-based segmentation for magnetic resonance brain images
  openalex Mariano Cabezas, Arnau Oliver, Xavier Lladó, Jordi Freixenet 等 2011-08-28 置信度 0.72 Atlas (anatomy)SegmentationComputer scienceArtificial intelligenceComputer vision
• Brain imaging of neuropathic pain
  openalex Xavier Moisset, Didier Bouhassira 2007-01-01 置信度 0.72 Neuropathic painAllodyniaChronic painMedicineNeuroimaging
• Non-invasive optical spectroscopy and imaging of human brain function
  Brain activity is associated with changes in optical properties of brain tissue. Optical measurements during brain activation can assess haemoglobin oxygenation, cytochrome-c-oxidase redox state, and two types of changes in light scattering reflecting either m…
  openalex Arno Villringer, Britton Chance 1997-10-01 置信度 0.72 Functional near-infrared spectroscopyNeuroimagingHuman brainOptical imagingBrain activity and meditation
• Auto-Context and Its Application to High-Level Vision Tasks and 3D Brain Image Segmentation
  The notion of using context information for solving high-level vision and medical image segmentation problems has been increasingly realized in the field. However, how to learn an effective and efficient context model, together with an image appearance model, …
  openalex Zhuowen Tu, Xiang Bai 2009-12-02 置信度 0.72 Discriminative modelArtificial intelligenceConditional random fieldComputer scienceSegmentation
• The Adolescent Brain Cognitive Development (ABCD) study: Imaging acquisition across 21 sites
  The ABCD study is recruiting and following the brain development and health of over 10,000 9-10 year olds through adolescence. The imaging component of the study was developed by the ABCD Data Analysis and Informatics Center (DAIC) and the ABCD Imaging Acquisi…
  openalex B.J. Casey, Tariq Cannonier, May I. Conley, Alexandra O. Cohen 等 2018-03-18 置信度 0.72 Generalizability theoryPsychologyNeuroimagingWorkgroupCognition
• MR brain image segmentation using an enhanced fuzzy C-means algorithm
  This paper presents a new algorithm for fuzzy segmentation of MR brain images. Starting from the standard FCM and its bias-corrected version BCFCM algorithm, by splitting up the two major steps of the latter, and by introducing a new factor, the amount of requ…
  openalex László Szilágyi, Zoltán Benyó, Sándor Miklós Szilágyi, Hartwig Adam 2004-06-21 置信度 0.72 Computer scienceImage segmentationSegmentationFuzzy logicArtificial intelligence
• A Paradigm Shift in Functional Brain Imaging
  ### Introduction The history of brain imaging has paralleled the growth of the Society for Neuroscience, from its inception in 1973 with the introduction of x-ray computed tomography (CT) to the present (for a historical review, see [Webb, 1990][1]; [Kevles, 1…
  openalex Marcus E. Raichle 2009-10-14 置信度 0.72 Paradigm shiftNeuroimagingNeuroscienceCognitive scienceFunctional imaging
• Faster permutation inference in brain imaging
  Permutation tests are increasingly being used as a reliable method for inference in neuroimaging analysis. However, they are computationally intensive. For small, non-imaging datasets, recomputing a model thousands of times is seldom a problem, but for large, …
  openalex Anderson M. Winkler, Gerard R. Ridgway, Gwenaëlle Douaud, Thomas E. Nichols 等 2016-06-07 置信度 0.72 InferencePermutation (music)NeuroimagingComputer scienceArtificial intelligence
• Classification of magnetic resonance brain images using wavelets as input to support vector machine and neural network
  openalex Sandeep Chaplot, L.M. Patnaik, N. R. Jagannathan 2006-01-01 置信度 0.72 Support vector machineArtificial intelligenceComputer scienceArtificial neural networkPattern recognition (psychology)
• A wearable multi-channel fNIRS system for brain imaging in freely moving subjects
  openalex Sophie K. Piper, Arne Krueger, Stefan Koch, Jan Mehnert 等 2013-06-28 置信度 0.72 NeuroimagingFunctional near-infrared spectroscopyComputer scienceWearable computerBrain activity and meditation
• Dopamine Transporter Brain Imaging to Assess the Effects of Pramipexole vs Levodopa on Parkinson Disease Progression
  CONTEXT: Pramipexole and levodopa are effective medications to treat motor symptoms of early Parkinson disease (PD). In vitro and animal studies suggest that pramipexole may protect and that levodopa may either protect or damage dopamine neurons. Neuroimaging …
  openalex Parkinson Study Group 2002-04-03 置信度 0.72 PramipexoleLevodopaMedicineDopamineDopamine transporter
• Brain Imaging Generation with Latent Diffusion Models
  openalex Walter Hugo Lopez Pinaya, Petru-Daniel Tudosiu, Jessica Dafflon, Pedro F. da Costa 等 2022-01-01 置信度 0.72 Computer scienceSynthetic dataArtificial intelligenceBiobankProbabilistic logic
• Three-dimensional locations and boundaries of motor and premotor cortices as defined by functional brain imaging: A meta-analysis
  openalex Mary A. Mayka, Daniel M. Corcos, Sue E. Leurgans, David E. Vaillancourt 2006-03-30 置信度 0.72 Premotor cortexNeurosciencePrimary motor cortexSomatosensory systemMotor cortex
• Functional Brain Imaging
  openalex C Binnie 1989-09-01 置信度 0.72 Functional Brain ImagingNeuroimagingNeuroscienceComputer sciencePsychology
• Spatial Transformation and Registration of Brain Images Using Elastically Deformable Models
  The development of algorithms for the spatial transformation and registration of tomographic brain images is a key issue in several clinical and basic science medical applications, including computer-aided neurosurgery, functional image analysis, and morphomet…
  openalex Christos Davatzikos 1997-05-01 置信度 0.72 Image warpingArtificial intelligenceTransformation (genetics)Image registrationComputer science
• Neuropsychological impairments in schizophrenia: Integration of performance-based and brain imaging findings.
  Until recently, the dominant view was that schizophrenia patients have limited, if any, neuropsychological impairments, and those that are observed are only secondary to the florid symptoms of the disorder. This view has dramatically changed. This review integ…
  openalex Abraham Reichenberg, Philip D. Harvey 2007-01-01 置信度 0.72 NeuropsychologySchizophrenia (object-oriented programming)NeuroimagingPsychologyExecutive functions
• Anatomic standardization: linear scaling and nonlinear warping of functional brain images.
  UNLABELLED: An automated method was proposed for anatomic standardization of PET scans in three dimensions, which enabled objective intersubject and cross-group comparisons of functional brain images. METHODS: The method involved linear scaling to correct an i…
  openalex Satoshi Minoshima, Robert A. Koeppe, K.A. Frey, David E. Kuhl 1994-09-01 置信度 0.72 Image warpingNormalization (sociology)ReproducibilityWhite matterArtificial intelligence
• Boosting Skull-Stripping Performance for Pediatric Brain Images
  Skull-stripping is the removal of background and non-brain anatomical features from brain images. While many skull-stripping tools exist, few target pediatric populations. With the emergence of multi-institutional pediatric data acquisition efforts to broaden …
  arxiv William Kelley, Nathan Ngo, Adrian V. Dalca, Bruce Fischl 等 2024-02-26T15:05:03Z 置信度 0.78 eess.IVcs.CVq-bio.QM
• Precise measurement of CMB polarisation from Dome-C: the BRAIN and CLOVER experiments
  The characterisation of CMB polarisation is one of the next challenge in observationnal cosmology. This is especially true for the so-called B-modes that are at least 3 order of magnitude lower than CMB temperature fluctuations. A precise measurement of the an…
  arxiv M. Piat, C. Rosset, the BRAIN, CLOVER Collaboration 2004-12-22T13:34:52Z 置信度 0.78 astro-ph
• Translating the future: Image-to-image translation for the prediction of future brain metabolism
  Alzheimer's disease (AD) is a progressive neurodegenerative disorder leading to cognitive decline. [$^{18}$F]-Fluorodeoxyglucose positron emission tomography ([$^{18}$F]-FDG PET) is used to monitor brain metabolism, aiding in the diagnosis and assessment of AD…
  arxiv Elena Doering, Merle C. Hönig, Tobias Deußer, Gerard N. Bischof 等 2024-02-06T16:02:51Z 置信度 0.78 eess.IVphysics.med-phq-bio.NC
• Domain-invariant feature learning in brain MR imaging for content-based image retrieval
  When conducting large-scale studies that collect brain MR images from multiple facilities, the impact of differences in imaging equipment and protocols at each site cannot be ignored, and this domain gap has become a significant issue in recent years. In this …
  arxiv Shuya Tobari, Shuhei Tomoshige, Hayato Muraki, Kenichi Oishi 等 2025-01-02T16:27:19Z 置信度 0.78 cs.LGcs.CVcs.IR
• Efficient embedding network for 3D brain tumor segmentation
  3D medical image processing with deep learning greatly suffers from a lack of data. Thus, studies carried out in this field are limited compared to works related to 2D natural image analysis, where very large datasets exist. As a result, powerful and efficient…
  arxiv Hicham Messaoudi, Ahror Belaid, Mohamed Lamine Allaoui, Ahcene Zetout 等 2020-11-22T16:17:29Z 置信度 0.78 cs.CV
• Evaluation and Analysis of Different Aggregation and Hyperparameter Selection Methods for Federated Brain Tumor Segmentation
  Availability of large, diverse, and multi-national datasets is crucial for the development of effective and clinically applicable AI systems in the medical imaging domain. However, forming a global model by bringing these datasets together at a central locatio…
  arxiv Ece Isik-Polat, Gorkem Polat, Altan Kocyigit, Alptekin Temizel 2022-02-16T07:49:04Z 置信度 0.78 cs.LGcs.AIcs.CVcs.DCeess.IV
• Orchestration of Starbirth Activity in Disk Galaxies: New Perspectives from Ultraviolet Imaging
  Ultraviolet imaging of nearby disk galaxies reveals the star-forming activity in these systems with unprecedented clarity. UV images recently obtained with the Shuttle-borne Ultraviolet Imaging Telescope (UIT) reveal a remarkable variety of star-forming morpho…
  arxiv William H. Waller, Theodore P. Stecher, the Ultraviolet Imaging Telescope, Science Team 1996-12-11T21:45:55Z 置信度 0.78 astro-ph
• BrainPainter: A software for the visualisation of brain structures, biomarkers and associated pathological processes
  We present BrainPainter, a software that automatically generates images of highlighted brain structures given a list of numbers corresponding to the output colours of each region. Compared to existing visualisation software (i.e. Freesurfer, SPM, 3D Slicer), B…
  arxiv Razvan V. Marinescu, Arman Eshaghi, Daniel C. Alexander, Polina Golland 2019-05-21T13:37:14Z 置信度 0.78 cs.GReess.IV
• A framework for rapid, reproducible, and high-fidelity whole-brain multi-pool CEST imaging at 3T
  Purpose: To develop and validate a framework for rapid, accurate, and reproducible whole-brain, multi-pool chemical exchange saturation transfer (CEST) imaging at 3T, addressing challenges of long acquisition times and confounding factors. Methods: A single-sh…
  arxiv Yupeng Wu, Siyuan Fang, Siyuan Wang, Caixia Fu 等 2025-02-24T09:19:46Z 置信度 0.78 physics.med-ph
• Computational Pathology for Brain Disorders
  Non-invasive brain imaging techniques allow understanding the behavior and macro changes in the brain to determine the progress of a disease. However, computational pathology provides a deeper understanding of brain disorders at cellular level, able to consoli…
  arxiv Gabriel Jimenez, Daniel Racoceanu 2023-01-13T14:09:02Z 置信度 0.78 eess.IVcs.CVcs.LG
• Multimodal Brain Visualization
  Current connectivity diagrams of human brain image data are either overly complex or overly simplistic. In this work we introduce simple yet accurate interactive visual representations of multiple brain image structures and the connectivity among them. We map …
  arxiv Saad Nadeem, Arie Kaufman 2016-08-02T19:02:40Z 置信度 0.78 cs.GRq-bio.NC
• Three-dimensional microtomographic imaging of human brain cortex
  This paper describes an x-ray microtomographic technique for imaging the three-dimensional structure of the human cerebral cortex. Neurons in the brain constitute a neural circuit as a three-dimensional network. The brain tissue is composed of light elements t…
  arxiv Ryuta Mizutani, Akihisa Takeuchi, Kentaro Uesugi, Masami Ohyama 等 2016-09-08T04:52:40Z 置信度 0.78 physics.bio-phphysics.med-phq-bio.NC
• Transfer Learning in Magnetic Resonance Brain Imaging: a Systematic Review
  Transfer learning refers to machine learning techniques that focus on acquiring knowledge from related tasks to improve generalization in the tasks of interest. In MRI, transfer learning is important for developing strategies that address the variation in MR i…
  arxiv Juan Miguel Valverde, Vandad Imani, Ali Abdollahzadeh, Riccardo De Feo 等 2021-02-02T14:59:05Z 置信度 0.78 eess.IVcs.CVcs.LG
• Automatic Landmarks Correspondence Detection in Medical Images with an Application to Deformable Image Registration
  Purpose: Deformable Image Registration (DIR) can benefit from additional guidance using corresponding landmarks in the images. However, the benefits thereof are largely understudied, especially due to the lack of automatic landmark detection methods for three-…
  arxiv Monika Grewal, Jan Wiersma, Henrike Westerveld, Peter A. N. Bosman 等 2021-09-06T20:16:27Z 置信度 0.78 cs.CV
• SynthStrip: Skull-Stripping for Any Brain Image
  The removal of non-brain signal from magnetic resonance imaging (MRI) data, known as skull-stripping, is an integral component of many neuroimage analysis streams. Despite their abundance, popular classical skull-stripping methods are usually tailored to image…
  arxiv Andrew Hoopes, Jocelyn S. Mora, Adrian V. Dalca, Bruce Fischl 等 2022-03-18T14:08:20Z 置信度 0.78 eess.IVcs.CVphysics.med-phq-bio.NC
• Montage based 3D Medical Image Retrieval from Traumatic Brain Injury Cohort using Deep Convolutional Neural Network
  Brain imaging analysis on clinically acquired computed tomography (CT) is essential for the diagnosis, risk prediction of progression, and treatment of the structural phenotypes of traumatic brain injury (TBI). However, in real clinical imaging scenarios, enti…
  arxiv Cailey I. Kerley, Yuankai Huo, Shikha Chaganti, Shunxing Bao 等 2018-12-10T21:58:01Z 置信度 0.78 cs.IRcs.LGstat.ML
• Reconstructing neuronal anatomy from whole-brain images
  Reconstructing multiple molecularly defined neurons from individual brains and across multiple brain regions can reveal organizational principles of the nervous system. However, high resolution imaging of the whole brain is a technically challenging and slow p…
  arxiv James Gornet, Kannan Umadevi Venkataraju, Arun Narasimhan, Nicholas Turner 等 2019-03-17T05:06:29Z 置信度 0.78 cs.CVcs.LGq-bio.NC
• Randomized Multiresolution Scanning in Focal and Fast E/MEG Sensing of Brain Activity with a Variable Depth
  We focus on electromagnetoencephalography imaging of the neural activity and, in particular, finding a robust estimate for the primary current distribution via the hierarchical Bayesian model (HBM). Our aim is to develop a reasonably fast maximum a posteriori …
  arxiv Atena Rezaei, Alexandra Koulouri, Sampsa Pursiainen 2020-02-11T09:22:06Z 置信度 0.78 math.NAeess.IV
• Approximate invariance of metabolic energy per synapse during development in mammalian brains
  During mammalian development the cerebral metabolic rate correlates qualitatively with synaptogenesis, and both often exhibit bimodal temporal profiles. Despite these non-monotonic dependencies, it is found based on empirical data for different mammals that re…
  arxiv Jan Karbowski 2012-04-17T21:51:34Z 置信度 0.78 q-bio.NCq-bio.TO
• A Semi-Supervised Learning Method for the Identification of Bad Exposures in Large Imaging Surveys
  As the data volume of astronomical imaging surveys rapidly increases, traditional methods for image anomaly detection, such as visual inspection by human experts, are becoming impractical. We introduce a machine-learning-based approach to detect poor-quality e…
  arxiv Yufeng Luo, Adam D. Myers, Alex Drlica-Wagner, Dario Dematties 等 2025-07-17T04:52:05Z 置信度 0.78 astro-ph.IMcs.AI
• Disentangling Brain Graphs: A Note on the Conflation of Network and Connectivity Analyses
  Understanding the human brain remains the Holy Grail in biomedical science, and arguably in all of the sciences. Our brains represent the most complex systems in the world (and some contend the universe) comprising nearly one hundred billion neurons with septi…
  arxiv Sean L. Simpson, Paul J. Laurienti 2016-02-02T14:11:40Z 置信度 0.78 q-bio.QMq-bio.NCstat.APstat.ME
• High-resolution Multi-spectral Imaging with Diffractive Lenses and Learned Reconstruction
  Spectral imaging is a fundamental diagnostic technique with widespread application. Conventional spectral imaging approaches have intrinsic limitations on spatial and spectral resolutions due to the physical components they rely on. To overcome these physical …
  arxiv Figen S. Oktem, Oğuzhan Fatih Kar, Can Deniz Bezek, Farzad Kamalabadi 2020-08-26T15:33:00Z 置信度 0.78 eess.IV
• Context Aware 3D UNet for Brain Tumor Segmentation
  Deep convolutional neural network (CNN) achieves remarkable performance for medical image analysis. UNet is the primary source in the performance of 3D CNN architectures for medical imaging tasks, including brain tumor segmentation. The skip connection in the …
  arxiv Parvez Ahmad, Saqib Qamar, Linlin Shen, Adnan Saeed 2020-10-25T10:32:25Z 置信度 0.78 eess.IVcs.CV
• Exact Imaging of Extended Targets Using Multistatic Interferometric Measurements
  In this paper, we present a novel approach that can exactly recover extended targets in wave-based multistatic interferometric imaging, based on Generalized Wirtinger Flow (GWF) theory [1]. Interferometric imaging is a generalization of phase retrieval, which …
  arxiv Bariscan Yonel, Il-Young Son, Birsen Yazici 2019-05-24T21:56:47Z 置信度 0.78 eess.SPeess.IV
• Mask of truth: model sensitivity to unexpected regions of medical images
  The development of larger models for medical image analysis has led to increased performance. However, it also affected our ability to explain and validate model decisions. Models can use non-relevant parts of images, also called spurious correlations or short…
  arxiv Théo Sourget, Michelle Hestbek-Møller, Amelia Jiménez-Sánchez, Jack Junchi Xu 等 2024-12-05T10:06:58Z 置信度 0.78 cs.CV
• Interferometric lensless imaging: rank-one projections of image frequencies with speckle illuminations
  Lensless illumination single-pixel imaging with a multicore fiber (MCF) is a computational imaging technique that enables potential endoscopic observations of biological samples at cellular scale. In this work, we show that this technique is tantamount to coll…
  arxiv Olivier Leblanc, Mathias Hofer, Siddharth Sivankutty, Hervé Rigneault 等 2023-06-22T07:05:02Z 置信度 0.78 eess.IVcs.ITphysics.optics
• HNF-Netv2 for Brain Tumor Segmentation using multi-modal MR Imaging
  In our previous work, $i.e.$, HNF-Net, high-resolution feature representation and light-weight non-local self-attention mechanism are exploited for brain tumor segmentation using multi-modal MR imaging. In this paper, we extend our HNF-Net to HNF-Netv2 by addi…
  arxiv Haozhe Jia, Chao Bai, Weidong Cai, Heng Huang 等 2022-02-10T06:34:32Z 置信度 0.78 eess.IVcs.CV
• Brain-optimized inference improves reconstructions of fMRI brain activity
  The release of large datasets and developments in AI have led to dramatic improvements in decoding methods that reconstruct seen images from human brain activity. We evaluate the prospect of further improving recent decoding methods by optimizing for consisten…
  arxiv Reese Kneeland, Jordyn Ojeda, Ghislain St-Yves, Thomas Naselaris 2023-12-12T20:08:59Z 置信度 0.78 q-bio.NCcs.AIcs.CVcs.LG
• Predicting Thrombectomy Recanalization from CT Imaging Using Deep Learning Models
  For acute ischemic stroke (AIS) patients with large vessel occlusions, clinicians must decide if the benefit of mechanical thrombectomy (MTB) outweighs the risks and potential complications following an invasive procedure. Pre-treatment computed tomography (CT…
  arxiv Haoyue Zhang, Jennifer S. Polson, Eric J. Yang, Kambiz Nael 等 2023-02-08T15:41:21Z 置信度 0.78 eess.IVcs.CV
• Image warp preserving content intensity
  An accurate method for warping images is presented. Differently from most commonly used techniques, this method guarantees the conservation of the intensity of the transformed image, evaluated as the sum of its pixel values over the whole image or over corresp…
  arxiv Enrico Segre 2022-07-13T14:55:46Z 置信度 0.78 cs.CVcs.CG
• MBDRes-U-Net: Multi-Scale Lightweight Brain Tumor Segmentation Network
  Accurate segmentation of brain tumors plays a key role in the diagnosis and treatment of brain tumor diseases. It serves as a critical technology for quantifying tumors and extracting their features. With the increasing application of deep learning methods, th…
  arxiv Longfeng Shen, Yanqi Hou, Jiacong Chen, Liangjin Diao 等 2024-11-04T09:03:43Z 置信度 0.78 eess.IVcs.AIcs.CV
• Predicting isocitrate dehydrogenase mutation status in glioma using structural brain networks and graph neural networks
  Glioma is a common malignant brain tumor with distinct survival among patients. The isocitrate dehydrogenase (IDH) gene mutation provides critical diagnostic and prognostic value for glioma. It is of crucial significance to non-invasively predict IDH mutation …
  arxiv Yiran Wei, Yonghao Li, Xi Chen, Carola-Bibiane Schönlieb 等 2021-09-04T12:19:33Z 置信度 0.78 eess.IVcs.CVq-bio.NC
• iCBIR-Sli: Interpretable Content-Based Image Retrieval with 2D Slice Embeddings
  Current methods for searching brain MR images rely on text-based approaches, highlighting a significant need for content-based image retrieval (CBIR) systems. Directly applying 3D brain MR images to machine learning models offers the benefit of effectively lea…
  arxiv Shuhei Tomoshige, Hayato Muraki, Kenichi Oishi, Hitoshi Iyatomi 2025-01-03T05:26:34Z 置信度 0.78 cs.CVcs.LGeess.IV
• NeuroNet: Fast and Robust Reproduction of Multiple Brain Image Segmentation Pipelines
  NeuroNet is a deep convolutional neural network mimicking multiple popular and state-of-the-art brain segmentation tools including FSL, SPM, and MALPEM. The network is trained on 5,000 T1-weighted brain MRI scans from the UK Biobank Imaging Study that have bee…
  arxiv Martin Rajchl, Nick Pawlowski, Daniel Rueckert, Paul M. Matthews 等 2018-06-11T20:21:23Z 置信度 0.78 cs.CVcs.LG
• The Potential of the Human Connectome as a Biomarker of Brain Disease
  The human connectome at the level of fiber tracts between brain regions has been shown to differ in patients with brain disorders compared to healthy control groups. Nonetheless, there is a potentially large number of different network organizations for indivi…
  arxiv Marcus Kaiser 2013-10-15T11:18:16Z 置信度 0.78 q-bio.NCphysics.med-ph
• HiDiff: Hybrid Diffusion Framework for Medical Image Segmentation
  Medical image segmentation has been significantly advanced with the rapid development of deep learning (DL) techniques. Existing DL-based segmentation models are typically discriminative; i.e., they aim to learn a mapping from the input image to segmentation m…
  arxiv Tao Chen, Chenhui Wang, Zhihao Chen, Yiming Lei 等 2024-07-03T23:59:09Z 置信度 0.78 cs.CV
• Self-Supervised Ultrasound to MRI Fetal Brain Image Synthesis
  Fetal brain magnetic resonance imaging (MRI) offers exquisite images of the developing brain but is not suitable for second-trimester anomaly screening, for which ultrasound (US) is employed. Although expert sonographers are adept at reading US images, MR imag…
  arxiv Jianbo Jiao, Ana I. L. Namburete, Aris T. Papageorghiou, J. Alison Noble 2020-08-19T22:56:36Z 置信度 0.78 eess.IVcs.CVcs.LG
• Brain Tumor Sequence Registration with Non-iterative Coarse-to-fine Networks and Dual Deep Supervision
  In this study, we focus on brain tumor sequence registration between pre-operative and follow-up Magnetic Resonance Imaging (MRI) scans of brain glioma patients, in the context of Brain Tumor Sequence Registration challenge (BraTS-Reg 2022). Brain tumor regist…
  arxiv Mingyuan Meng, Lei Bi, Dagan Feng, Jinman Kim 2022-11-15T03:58:47Z 置信度 0.78 cs.CV
• Group-level Brain Decoding with Deep Learning
  Decoding brain imaging data are gaining popularity, with applications in brain-computer interfaces and the study of neural representations. Decoding is typicallysubject-specific and does not generalise well over subjects, due to high amounts ofbetween subject …
  arxiv Richard Csaky, Mats Van Es, Oiwi Parker Jones, Mark Woolrich 2022-05-27T17:12:26Z 置信度 0.78 cs.LGeess.SPq-bio.NC
• Reproducibility Evaluation of SLANT Whole Brain Segmentation Across Clinical Magnetic Resonance Imaging Protocols
  Whole brain segmentation on structural magnetic resonance imaging (MRI) is essential for understanding neuroanatomical-functional relationships. Traditionally, multi-atlas segmentation has been regarded as the standard method for whole brain segmentation. In p…
  arxiv Yunxi Xiong, Yuankai Huo, Jiachen Wang, L. Taylor Davis 等 2019-01-07T19:57:07Z 置信度 0.78 cs.CV
• Unveiling the mystery of visual information processing in human brain
  It is generally accepted that human vision is an extremely powerful information processing system that facilitates our interaction with the surrounding world. However, despite extended and extensive research efforts, which encompass many exploration fields, th…
  arxiv Emanuel Diamant 2008-07-02T12:33:48Z 置信度 0.78 cs.AIcs.IRcs.ITq-bio.NC
• Brain Decodes Deep Nets
  We developed a tool for visualizing and analyzing large pre-trained vision models by mapping them onto the brain, thus exposing their hidden inside. Our innovation arises from a surprising usage of brain encoding: predicting brain fMRI measurements in response…
  arxiv Huzheng Yang, James Gee, Jianbo Shi 2023-12-03T04:36:04Z 置信度 0.78 cs.CV
• Isointense infant brain MRI segmentation with a dilated convolutional neural network
  Quantitative analysis of brain MRI at the age of 6 months is difficult because of the limited contrast between white matter and gray matter. In this study, we use a dilated triplanar convolutional neural network in combination with a non-dilated 3D convolution…
  arxiv Pim Moeskops, Josien P. W. Pluim 2017-08-09T08:49:12Z 置信度 0.78 cs.CV
• Identifying partial mouse brain microscopy images from Allen reference atlas using a contrastively learned semantic space
  Precise identification of mouse brain microscopy images is a crucial first step when anatomical structures in the mouse brain are to be registered to a reference atlas. Practitioners usually rely on manual comparison of images or tools that assume the presence…
  arxiv Justinas Antanavicius, Roberto Leiras, Raghavendra Selvan 2021-09-14T13:11:34Z 置信度 0.78 cs.CVcs.LGstat.ML
• BigGAN-based Bayesian reconstruction of natural images from human brain activity
  In the visual decoding domain, visually reconstructing presented images given the corresponding human brain activity monitored by functional magnetic resonance imaging (fMRI) is difficult, especially when reconstructing viewed natural images. Visual reconstruc…
  arxiv Kai Qiao, Jian Chen, Linyuan Wang, Chi Zhang 等 2020-03-13T04:32:11Z 置信度 0.78 cs.CVcs.LGeess.IVq-bio.NC
• LearnAD: Learning Interpretable Rules for Brain Networks in Alzheimer's Disease Classification
  We introduce LearnAD, a neuro-symbolic method for predicting Alzheimer's disease from brain magnetic resonance imaging data, learning fully interpretable rules. LearnAD applies statistical models, Decision Trees, Random Forests, or GNNs to identify relevant br…
  arxiv Thomas Andrews, Mark Law, Sara Ahmadi-Abhari, Alessandra Russo 2025-12-30T23:30:18Z 置信度 0.78 cs.LGcs.AI
• Brain Surface Reconstruction from MRI Images Based on Segmentation Networks Applying Signed Distance Maps
  Whole-brain surface extraction is an essential topic in medical imaging systems as it provides neurosurgeons with a broader view of surgical planning and abnormality detection. To solve the problem confronted in current deep learning skull stripping methods la…
  arxiv Heng Fang, Xi Yang, Taichi Kin, Takeo Igarashi 2021-04-09T10:24:27Z 置信度 0.78 cs.CVcs.LGeess.IV
• ReFuSeg: Regularized Multi-Modal Fusion for Precise Brain Tumour Segmentation
  Semantic segmentation of brain tumours is a fundamental task in medical image analysis that can help clinicians in diagnosing the patient and tracking the progression of any malignant entities. Accurate segmentation of brain lesions is essential for medical di…
  arxiv Aditya Kasliwal, Sankarshanaa Sagaram, Laven Srivastava, Pratinav Seth 等 2023-08-26T13:41:56Z 置信度 0.78 eess.IVcs.CV
• Enhancing Angular Resolution via Directionality Encoding and Geometric Constraints in Brain Diffusion Tensor Imaging
  Diffusion-weighted imaging (DWI) is a type of Magnetic Resonance Imaging (MRI) technique sensitised to the diffusivity of water molecules, offering the capability to inspect tissue microstructures and is the only in-vivo method to reconstruct white matter fibe…
  arxiv Sheng Chen, Zihao Tang, Mariano Cabezas, Xinyi Wang 等 2024-09-11T11:12:26Z 置信度 0.78 cs.CVcs.AI
• Subject-Specific Lesion Generation and Pseudo-Healthy Synthesis for Multiple Sclerosis Brain Images
  Understanding the intensity characteristics of brain lesions is key for defining image-based biomarkers in neurological studies and for predicting disease burden and outcome. In this work, we present a novel foreground-based generative method for modelling the…
  arxiv Berke Doga Basaran, Mengyun Qiao, Paul M. Matthews, Wenjia Bai 2022-08-03T15:12:55Z 置信度 0.78 eess.IVcs.CVcs.LG
• SADM: Sequence-Aware Diffusion Model for Longitudinal Medical Image Generation
  Human organs constantly undergo anatomical changes due to a complex mix of short-term (e.g., heartbeat) and long-term (e.g., aging) factors. Evidently, prior knowledge of these factors will be beneficial when modeling their future state, i.e., via image genera…
  arxiv Jee Seok Yoon, Chenghao Zhang, Heung-Il Suk, Jia Guo 等 2022-12-16T01:35:27Z 置信度 0.78 cs.CVcs.AIcs.LG
• Multiparametric Deep Learning and Radiomics for Tumor Grading and Treatment Response Assessment of Brain Cancer: Preliminary Results
  Radiomics is an exciting new area of texture research for extracting quantitative and morphological characteristics of pathological tissue. However, to date, only single images have been used for texture analysis. We have extended radiomic texture methods to u…
  arxiv Vishwa S. Parekh, John Laterra, Chetan Bettegowda, Alex E. Bocchieri 等 2019-06-10T14:57:05Z 置信度 0.78 eess.IVcs.LGphysics.med-phq-bio.QM
• Explainable Image Similarity: Integrating Siamese Networks and Grad-CAM
  With the proliferation of image-based applications in various domains, the need for accurate and interpretable image similarity measures has become increasingly critical. Existing image similarity models often lack transparency, making it challenging to unders…
  arxiv Ioannis E. Livieris, Emmanuel Pintelas, Niki Kiriakidou, Panagiotis Pintelas 2023-10-11T17:21:48Z 置信度 0.78 cs.CVcs.AIcs.LG
• Root-Cause Analysis of Activation Cascade Differences in Brain Networks
  Diffusion MRI imaging and tractography algorithms have enabled the mapping of the macro-scale connectome of the entire brain. At the functional level, probably the simplest way to study the dynamics of macro-scale brain activity is to compute the "activation c…
  arxiv Qihang Yao, Manoj Chandrasekaran, Constantine Dovrolis 2022-07-16T15:07:30Z 置信度 0.78 q-bio.NC
• Diminishing Uncertainty within the Training Pool: Active Learning for Medical Image Segmentation
  Active learning is a unique abstraction of machine learning techniques where the model/algorithm could guide users for annotation of a set of data points that would be beneficial to the model, unlike passive machine learning. The primary advantage being that a…
  arxiv Vishwesh Nath, Dong Yang, Bennett A. Landman, Daguang Xu 等 2021-01-07T01:55:48Z 置信度 0.78 cs.CV
• Automatic Brain Tumor Segmentation with Scale Attention Network
  Automatic segmentation of brain tumors is an essential but challenging step for extracting quantitative imaging biomarkers for accurate tumor detection, diagnosis, prognosis, treatment planning and assessment. Multimodal Brain Tumor Segmentation Challenge 2020…
  arxiv Yading Yuan 2020-11-06T04:45:49Z 置信度 0.78 eess.IVcs.CV
• Global and regional brain metabolic scaling and its functional consequences
  Background: Information processing in the brain requires large amounts of metabolic energy, the spatial distribution of which is highly heterogeneous reflecting complex activity patterns in the mammalian brain. Results: Here, it is found based on empirical dat…
  arxiv Jan Karbowski 2007-05-21T04:13:41Z 置信度 0.78 q-bio.NCq-bio.TO
• PWLS-ULTRA: An Efficient Clustering and Learning-Based Approach for Low-Dose 3D CT Image Reconstruction
  The development of computed tomography (CT) image reconstruction methods that significantly reduce patient radiation exposure while maintaining high image quality is an important area of research in low-dose CT (LDCT) imaging. We propose a new penalized weight…
  arxiv Xuehang Zheng, Saiprasad Ravishankar, Yong Long, Jeffrey A. Fessler 2017-03-27T16:16:35Z 置信度 0.78 stat.ML
• ACE-Brain-0: Spatial Intelligence as a Shared Scaffold for Universal Embodiments
  Universal embodied intelligence demands robust generalization across heterogeneous embodiments, such as autonomous driving, robotics, and unmanned aerial vehicles (UAVs). However, existing embodied brain in training a unified model over diverse embodiments fre…
  arxiv Ziyang Gong, Zehang Luo, Anke Tang, Zhe Liu 等 2026-03-03T17:53:45Z 置信度 0.78 cs.ROcs.CLcs.CV
• Modeling the Sequence of Brain Volumes by Local Mesh Models for Brain Decoding
  We represent the sequence of fMRI (Functional Magnetic Resonance Imaging) brain volumes recorded during a cognitive stimulus by a graph which consists of a set of local meshes. The corresponding cognitive process, encoded in the brain, is then represented by t…
  arxiv Itir Onal, Mete Ozay, Eda Mizrak, Ilke Oztekin 等 2016-03-03T12:06:00Z 置信度 0.78 cs.LGcs.AIcs.CV
• Quantum Physics in Neuroscience and Psychology: A New Theory With Respect to Mind/Brain Interaction
  The cognitive frame in which most neuropsychological research on the neural basis of behavior is conducted contains the assumption that brain mechanisms per se fully suffice to explain all psychologically described phenomena. This assumption stems from the ide…
  arxiv J. M. Schwartz, H. P. Stapp, M. Beauregard 2004-01-14T22:23:39Z 置信度 0.78 q-bio.NC
• BIQ2021: A Large-Scale Blind Image Quality Assessment Database
  The assessment of the perceptual quality of digital images is becoming increasingly important as a result of the widespread use of digital multimedia devices. Smartphones and high-speed internet are just two examples of technologies that have multiplied the am…
  arxiv Nisar Ahmed, Shahzad Asif 2022-02-08T14:07:38Z 置信度 0.78 cs.CVeess.IV
• Snapshot multispectral imaging using a filter array
  A multispectral filter array (MSFA) is one solution for capturing a multispectral image (MSI) in a single shot at low cost. We introduce our optimization method of the spectral sensitivity of the MSFAs and demosaicking, and show a new prototype filter array fo…
  arxiv Kazuma Shinoda 2018-08-28T04:04:47Z 置信度 0.78 eess.IV
• MedEdit: Counterfactual Diffusion-based Image Editing on Brain MRI
  Denoising diffusion probabilistic models enable high-fidelity image synthesis and editing. In biomedicine, these models facilitate counterfactual image editing, producing pairs of images where one is edited to simulate hypothetical conditions. For example, the…
  arxiv Malek Ben Alaya, Daniel M. Lang, Benedikt Wiestler, Julia A. Schnabel 等 2024-07-21T21:19:09Z 置信度 0.78 eess.IVcs.CV
• Unsupervised Segmentation of 3D Medical Images Based on Clustering and Deep Representation Learning
  This paper presents a novel unsupervised segmentation method for 3D medical images. Convolutional neural networks (CNNs) have brought significant advances in image segmentation. However, most of the recent methods rely on supervised learning, which requires la…
  arxiv Takayasu Moriya, Holger R. Roth, Shota Nakamura, Hirohisa Oda 等 2018-04-11T06:30:30Z 置信度 0.78 cs.CV
• Deep learning and its application to medical image segmentation
  One of the most common tasks in medical imaging is semantic segmentation. Achieving this segmentation automatically has been an active area of research, but the task has been proven very challenging due to the large variation of anatomy across different patien…
  arxiv Holger R. Roth, Chen Shen, Hirohisa Oda, Masahiro Oda 等 2018-03-23T08:55:10Z 置信度 0.78 cs.CV
• Brain-Semantoks: Learning Semantic Tokens of Brain Dynamics with a Self-Distilled Foundation Model
  The development of foundation models for functional magnetic resonance imaging (fMRI) time series holds significant promise for predicting phenotypes related to disease and cognition. Current models, however, are often trained using a mask-and-reconstruct obje…
  arxiv Sam Gijsen, Marc-Andre Schulz, Kerstin Ritter 2025-12-12T14:11:20Z 置信度 0.78 cs.LGcs.CVq-bio.NC