James C. Gee
A5005451810- Medical Image Segmentation Techniques
- Advanced Neuroimaging Techniques and Applications
- Functional Brain Connectivity Studies
- Advanced MRI Techniques and Applications
- Radiomics and Machine Learning in Medical Imaging
- Medical Imaging Techniques and Applications
- Fetal and Pediatric Neurological Disorders
- Cell Image Analysis Techniques
- Image Retrieval and Classification Techniques
- AI in cancer detection
- Morphological variations and asymmetry
- Dementia and Cognitive Impairment Research
- Alzheimer's disease research and treatments
- Retinal Imaging and Analysis
- 3D Shape Modeling and Analysis
- Medical Imaging and Analysis
- Advanced Vision and Imaging
- Neurobiology of Language and Bilingualism
- Atomic and Subatomic Physics Research
- Advanced Image and Video Retrieval Techniques
- Single-cell and spatial transcriptomics
- Robotics and Sensor-Based Localization
- Lung Cancer Diagnosis and Treatment
- Image and Object Detection Techniques
- Tensor decomposition and applications
California University of Pennsylvania
2005-2025
University of Pennsylvania
2016-2025
Penn Center for AIDS Research
2011-2024
Hospital of the University of Pennsylvania
2014-2020
Philadelphia University
2007-2020
University of Virginia
2020
Committee on Publication Ethics
2020
Radiology Associates
2020
University of California, San Francisco
2020
Penn Presbyterian Medical Center
2020
A variant of the popular nonparametric nonuniform intensity normalization (N3) algorithm is proposed for bias field correction. Given superb performance N3 and its public availability, it has been subject several evaluation studies. These studies have demonstrated importance certain parameters associated with B-spline least-squares fitting. We propose substitution a recently developed fast robust approximation routine modified hierarchical optimization scheme improved correction over...
We address the problem of applying spatial transformations (or "image warps") to diffusion tensor magnetic resonance images. The orientational information that these images contain must be handled appropriately when they are transformed spatially during image registration. present solutions for global three-dimensional up 12-parameter affine complexity and indicate how our methods can extended higher order transformations. Several approaches presented tested using synthetic data. One method,...
Publicly available scientific resources help establish evaluation standards, provide a platform for teaching and improve reproducibility. Version 4 of the Insight ToolKit (ITK(4)) seeks to new standards in publicly image registration methodology. ITK(4) makes several advances comparison previous versions ITK. supports both multivariate images objective functions; it also unifies high-dimensional (deformation field) low-dimensional (affine) transformations with metrics that are reusable...
Here we report the generation of a multimodal cell census and atlas mammalian primary motor cortex as initial product BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved morphological electrophysiological properties cellular resolution input-output mapping, integrated through cross-modal computational analysis. Our results advance collective knowledge...
Individuals who experience early adversity, such as child maltreatment, are at heightened risk for a broad array of social and health difficulties. However, little is known about how this behavioral instantiated in the brain. Here we examine neurobiological contribution to individual differences human behavior using methodology appropriate use with pediatric populations paired an in-depth measure behavior. We show that alterations orbitofrontal cortex among individuals experienced physical...
EMPIRE10 (Evaluation of Methods for Pulmonary Image REgistration 2010) is a public platform fair and meaningful comparison registration algorithms which are applied to database intrapatient thoracic CT image pairs. Evaluation nonrigid techniques nontrivial task. This compounded by the fact that researchers typically test only on their own data, varies widely. For this reason, reliable assessment different has been virtually impossible in past. In work we present results launch phase...
The mammalian brain consists of millions to billions cells that are organized into many cell types with specific spatial distribution patterns and structural functional properties1-3. Here we report a comprehensive high-resolution transcriptomic cell-type atlas for the whole adult mouse brain. was created by combining single-cell RNA-sequencing (scRNA-seq) dataset around 7 million profiled (approximately 4.0 passing quality control), approximately 4.3 using multiplexed error-robust...
An essential step toward understanding brain function is to establish a structural framework with cellular resolution on which multi-scale datasets spanning molecules, cells, circuits and systems can be integrated interpreted
Abstract The Advanced Normalizations Tools ecosystem, known as ANTsX, consists of multiple open-source software libraries which house top-performing algorithms used worldwide by scientific and research communities for processing analyzing biological medical imaging data. base library, ANTs, is built upon, contributes to, the NIH-sponsored Insight Toolkit. Founded in 2008 with highly regarded Symmetric Normalization image registration framework, ANTs library has since grown to include...
The mammalian brain is composed of millions to billions cells that are organized into numerous cell types with specific spatial distribution patterns and structural functional properties. An essential step towards understanding function obtain a parts list, i.e., catalog types, the brain. Here, we report comprehensive high-resolution transcriptomic type atlas for whole adult mouse was created based on combination two single-cell-level, whole-brain-scale datasets: single-cell RNA-sequencing...
Feature matching, which refers to establishing the correspondence of regions between two images (usually voxel features), is a crucial prerequisite feature-based registration. For deformable image registration tasks, traditional methods typically use an iterative matching strategy for interest region where feature selection and are explicit, but specific schemes often useful in solving application-specific problems require several minutes each In past few years, feasibility learning-based...