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An open challenge problem at the forefront of modern neuroscience is to obtain a comprehensive mapping of the neural pathways that underlie human brain function; an enhanced understanding of the wiring diagram of the brain promises to lead…

There are multiple scales of abstraction from which we can describe the same image, depending on whether we are focusing on fine-grained details or a more global attribute of the image. In brain mapping, learning to automatically parse…

We propose a unified appearance model accounting for traditional shallow (i.e. 3D SIFT keypoints) and deep (i.e. CNN output layers) image feature representations, encoding respectively specific, localized neuroanatomical patterns and rich…

Computer Vision and Pattern Recognition · Computer Science 2020-10-22 L. Chauvin , M. Ben Lazreg , J. B. Carluer , W. Wells , M. Toews

Light sheet fluorescence microscopy (LSM) enables high-resolution, three-dimensional (3D) imaging of biological specimens, providing rich volumetric data for studying cellular organization, pathology, and vascular networks. However, the…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Adina Scheinfeld , Haotan Zhang , Shang Mu , Rudolf L. M. van Herten , Lucas Stoffl , Ali Erturk , Zhuhao Wu , Johannes C. Paetzold

Understanding how the human brain represents visual concepts, and in which brain regions these representations are encoded, remains a long-standing challenge. Decades of work have advanced our understanding of visual representations, yet…

Computer Vision and Pattern Recognition · Computer Science 2025-12-15 Navve Wasserman , Matias Cosarinsky , Yuval Golbari , Aude Oliva , Antonio Torralba , Tamar Rott Shaham , Michal Irani

Early infancy is a rapid and dynamic neurodevelopmental period for behavior and neurocognition. Longitudinal magnetic resonance imaging (MRI) is an effective tool to investigate such a crucial stage by capturing the developmental…

Image and Video Processing · Electrical Eng. & Systems 2024-02-22 Lianghu Guo , Tianli Tao , Xinyi Cai , Zihao Zhu , Jiawei Huang , Lixuan Zhu , Zhuoyang Gu , Haifeng Tang , Rui Zhou , Siyan Han , Yan Liang , Qing Yang , Dinggang Shen , Han Zhang

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…

Graphics · Computer Science 2016-09-02 Saad Nadeem , Arie Kaufman

Magnetic resonance imaging~(MRI) have played a crucial role in brain disease diagnosis, with which a range of computer-aided artificial intelligence methods have been proposed. However, the early explorations usually focus on the limited…

Computer Vision and Pattern Recognition · Computer Science 2023-09-14 Jiayu Lei , Lisong Dai , Haoyun Jiang , Chaoyi Wu , Xiaoman Zhang , Yao Zhang , Jiangchao Yao , Weidi Xie , Yanyong Zhang , Yuehua Li , Ya Zhang , Yanfeng Wang

Maps of brain microarchitecture are important for understanding neurological function and behavior, including alterations caused by chronic conditions such as neurodegenerative disease. Techniques such as knife-edge scanning microscopy…

Image and Video Processing · Electrical Eng. & Systems 2020-02-06 Leila Saadatifard , Aryan Mobiny , Pavel Govyadinov , Hien Nguyen , David Mayerich

Reconstructing a map of neuronal connectivity is a critical challenge in contemporary neuroscience. Recent advances in high-throughput serial section electron microscopy (EM) have produced massive 3D image volumes of nanoscale brain tissue…

Deep learning has demonstrated remarkable success in medical image segmentation and computer-aided diagnosis. In particular, numerous advanced methods have achieved state-of-the-art performance in brain tumor segmentation from MRI scans.…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Xiaoyu Shi , Rahul Kumar Jain , Yinhao Li , Ruibo Hou , Jingliang Cheng , Jie Bai , Guohua Zhao , Lanfen Lin , Rui Xu , Yen-wei Chen

Brain signal visualization has emerged as an active research area, serving as a critical interface between the human visual system and computer vision models. Although diffusion models have shown promise in analyzing functional magnetic…

Computer Vision and Pattern Recognition · Computer Science 2023-12-19 Bohan Zeng , Shanglin Li , Xuhui Liu , Sicheng Gao , Xiaolong Jiang , Xu Tang , Yao Hu , Jianzhuang Liu , Baochang Zhang

Reconstructing and understanding 3D structures from a limited number of images is a well-established problem in computer vision. Traditional methods usually break this task into multiple subtasks, each requiring complex transformations…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Zhiwen Fan , Jian Zhang , Wenyan Cong , Peihao Wang , Renjie Li , Kairun Wen , Shijie Zhou , Achuta Kadambi , Zhangyang Wang , Danfei Xu , Boris Ivanovic , Marco Pavone , Yue Wang

Automated sample preparation and electron microscopy enables acquisition of very large image data sets. These technical advances are of special importance to the field of neuroanatomy, as 3D reconstructions of neuronal processes at the nm…

Understanding how the brain represents visual information is a fundamental challenge in neuroscience and artificial intelligence. While AI-driven decoding of neural data has provided insights into the human visual system, integrating…

Neural and Evolutionary Computing · Computer Science 2025-10-07 Dongyang Li , Haoyang Qin , Mingyang Wu , Chen Wei , Quanying Liu

Segmenting 3D cell nuclei from microscopy image volumes is critical for biological and clinical analysis, enabling the study of cellular expression patterns and cell lineages. However, current datasets for neuronal nuclei usually contain…

Mapping blood microflows of the whole brain is crucial for early diagnosis of cerebral diseases. Ultrasound localization microscopy (ULM) was recently applied to map and quantify blood microflows in 2D in the brain of adult patients down to…

Medical Physics · Physics 2023-04-12 Hugues Favre , Mathieu Pernot , Mickael Tanter , Clément Papadacci

Whole-brain parcellation from MRI is a critical yet challenging task due to the complexity of subdividing the brain into numerous small, irregular shaped regions. Traditionally, template-registration methods were used, but recent advances…

Computer Vision and Pattern Recognition · Computer Science 2026-01-15 Yucheng Li , Xiaofan Wang , Junyi Wang , Yijie Li , Xi Zhu , Mubai Du , Dian Sheng , Wei Zhang , Fan Zhang

Three-dimensional Morphable Models (3DMMs) are powerful statistical tools for representing the 3D shapes and textures of an object class. Here we present the most complete 3DMM of the human head to date that includes face, cranium, ears,…

Computer Vision and Pattern Recognition · Computer Science 2020-02-21 Stylianos Ploumpis , Evangelos Ververas , Eimear O' Sullivan , Stylianos Moschoglou , Haoyang Wang , Nick Pears , William A. P. Smith , Baris Gecer , Stefanos Zafeiriou

Synchrotron radiation-based X-ray microtomography is uniquely suited for post mortem three-dimensional visualization of organs such as the mouse brain. Tomographic imaging of the entire mouse brain with isotropic cellular resolution…