Probabilistic atlases are widely used in the neuroscience community as a tool for providing a standard space for comparison of subjects and as tissue priors used to enhance the intensity-based classification of brain MRI. Most efforts so far have focused on static brain atlases either for adult or pediatric cohorts. In contrast to the adult brain the rapid growth of the neonatal brain requires an age-specific spatial probabilistic atlas to provide suitable anatomical and structural information. In this paper we describe a 4D probabilistic atlas that allows dynamic generation of prior tissue probability maps for any chosen stage of neonatal brain development between 29 and 44 gestational weeks. The atlas is created from the segmentations of 142 neonatal subjects at different ages using a kernel-based regression method and provides prior tissue probability maps for six structures - cortex, white matter, subcortical grey matter, brainstem, cerebellum and cerebro-spinal fluid. The atlas is publicly available at www.brain-development.org.
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http://dx.doi.org/10.1016/j.neuroimage.2010.10.019 | DOI Listing |
Netw Neurosci
December 2024
Department of Clinical Cognition Science, Clinic of Neurology at the RWTH Aachen University Faculty of Medicine, ZBMT, Aachen, Germany.
Networks in the parietal and premotor cortices enable essential human abilities regarding motor processing, including attention and tool use. Even though our knowledge on its topography has steadily increased, a detailed picture of hemisphere-specific integrating pathways is still lacking. With the help of multishell diffusion magnetic resonance imaging, probabilistic tractography, and the Graph Theory Analysis, we investigated connectivity patterns between frontal premotor and posterior parietal brain areas in healthy individuals.
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December 2024
Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
It is now understood that brain metastases do not occur randomly but have distinct spatial patterns depending on the origin of the cancer. According to the "seed and soil" hypothesis, the final colonization of metastatic cells is the result of their adaptation to the altered environment. To investigate the most favorable microenvironment for brain metastasis, we analyzed neuroimaging data from 177 patients with breast cancer brain metastasis and 548 patients with lung cancer brain metastasis to create a replicable probabilistic map of metastatic locations.
View Article and Find Full Text PDFNMR Biomed
February 2025
Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China.
This study aimed to develop an automatic segmentation method for brainstem fiber bundles. We utilized the brainstem as a seed region for probabilistic tractography based on multishell, multitissue constrained spherical deconvolution in 40 subjects from the Human Connectome Project (HCP). All tractography data were registered into a common space to construct a brainstem fiber cluster atlas.
View Article and Find Full Text PDFSci Rep
November 2024
The First Laboratory of Cancer Institute, The First Hospital of China Medical University, NO.155, North Nanjing Street, Heping District, Shenyang City, 110001, China.
The aim of this study was to develop a quantitative feature-based model from histopathologic images to assess the prognosis of patients with gastric cancer. Whole slide image (WSI) images of H&E-stained histologic specimens of gastric cancer patients from The Cancer Genome Atlas were included and randomly assigned to training and test groups in a 7:3 ratio. A systematic preprocessing approach was employed as well as a non-overlapping segmentation method that combined patch-level prediction with a multi-instance learning approach to integrate features across the slide images.
View Article and Find Full Text PDFCommun Med (Lond)
November 2024
Artificial Intelligence in Healthcare and Medicine, School of Computation, Information and Technology, Technical University of Munich, Munich, Germany.
Background: Reliable reference data in medical imaging is largely unavailable. Developing tools that allow for the comparison of individual patient data to reference data has a high potential to improve diagnostic imaging. Population atlases are a commonly used tool in medical imaging to facilitate this.
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