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Relevant bibliographies by topics / Corpus callosum shape

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Academic literature on the topic 'Corpus callosum shape'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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Journal articles on the topic "Corpus callosum shape"

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Walterfang, Mark, Gin S. Malhi, Amanda G. Wood, et al. "Corpus Callosum Size and Shape in Established Bipolar Affective Disorder." Australian & New Zealand Journal of Psychiatry 43, no. 9 (2009): 838–45. http://dx.doi.org/10.1080/00048670903107534.

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Objective: Callosal structural and functional alterations have been demonstrated in a range of neuropsychiatric illnesses, including bipolar disorder, but no study has examined regional callosal thickness in this phenotype. The aim of the present study was therefore to examine callosal size and shape in a well-defined group of bipolar affective disorder patients and controls. Methods: The participants included 24 patients with DSM-IV bipolar I disorder and 24 matched healthy controls. The corpus callosum was extracted from mid-callosal images from T1-weighted magnetic resonance imaging scans o

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Walsh, Erin I., Marnie E. Shaw, Daniela A. Espinoza Oyarce, Mark Fraser, and Nicolas Cherbuin. "Assumption-Free Assessment of Corpus Callosum Shape: Benchmarking and Application." Concepts in Magnetic Resonance Part A 2019 (July 1, 2019): 1–10. http://dx.doi.org/10.1155/2019/8921901.

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Shape analysis provides a unique insight into biological processes. This paper evaluates the properties, performance, and utility of elliptical Fourier (eFourier) analysis to operationalise global shape, focussing on the human corpus callosum. 8000 simulated corpus callosum contours were generated, systematically varying in terms of global shape (midbody arch, splenium size), local complexity (surface smoothness), and nonshape characteristics (e.g., rotation). 2088 real corpus callosum contours were manually traced from the PATH study. Performance of eFourier was benchmarked in terms of its ca

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Hampson, Elizabeth. "Is the size of the human corpus callosum influenced by sex hormones?" Behavioral and Brain Sciences 21, no. 3 (1998): 331–32. http://dx.doi.org/10.1017/s0140525x98271214.

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Fitch & Denenberg have shown that manipulations of ovarian and testicular hormones early in development can influence the adult size of the corpus callosum in the rat. The human corpus callosum is highly variable in size and shape, but data are only now beginning to emerge on whether sex steroids influence callosal differentiation in humans. I describe recent data from our own laboratory and suggest avenues for future research.

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Boiagina, Olga, Oleksandr Stepanenko, and Anastasiia Lebedieva. "Correlation Between Corpus Callosum Shape and Craniometric Measurements According to Mri Data." BRAIN. BROAD RESEARCH IN ARTIFICIAL INTELLIGENCE AND NEUROSCIENCE 12, no. 3 (2021): 01–10. http://dx.doi.org/10.18662/brain/12.3/216.

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The correlation between the cranial height and the height of the corpus callosum trunk bulge, and the relationship between the corpus callosum shape and the cranial shape have not been studied. The purpose of the article was to determine the individual variability of the corpus callosum height and shape of adults, and their dependence on the cranial height and shape. The material was two samples from a series of MR scans of the head of men and women of the second period of adulthood (19 variations in each group) without the central nervous system pathology. Magnetic resonance tomographic scann

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Walterfang, Mark, Amanda G. Wood, David C. Reutens, et al. "Morphology of the corpus callosum at different stages of schizophrenia: Cross-sectional study in first-episode and chronic illness." British Journal of Psychiatry 192, no. 6 (2008): 429–34. http://dx.doi.org/10.1192/bjp.bp.107.041251.

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BackgroundThe shape of the corpus callosum may differ in schizophrenia, although no study has compared first-episode with established illness.AimsTo investigate the size and shape of the corpus callosum in a large sample of people with first-episode and established schizophrenia.MethodCallosal size and shape were determined using highresolution magnetic resonance imaging on 76 patients with first-episode schizophrenia-spectrum disorders, 86 patients with established schizophrenia and 55 healthy participants.ResultsThere were no significant differences in total area across groups. Reductions in

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Olga, BOIAGINA, STEPANENKO Oleksandr, and LEBEDIEVA Anastasiia. "Correlation between Corpus Callosum Shape and Craniometric Measurements According to MRI Data." BRAIN. Broad Research in Artificial Intelligence and Neuroscience 12, no. 3 (2025): 01–10. https://doi.org/10.18662/brain/12.3/216.

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 The correlation between the cranial height and the height of the corpus callosum trunk bulge, and the relationship between the corpus callosum shape and the cranial shape have not been studied. The purpose of the article was to determine the individual variability of the corpus callosum height and shape of adults, and their dependence on the cranial height and shape. The material was two samples from a series of MR scans of the head of men and women of the second period of adulthood (19 variations in each group) without the central nervous system p

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FERRARIO, VIRGILIO F., CHIARELLA SFORZA, GRAZIANO SERRAO, TIZIANO FRATTINI, and CARLO DEL FAVERO. "Shape of the Human Corpus Callosum." Investigative Radiology 29, no. 7 (1994): 677–81. http://dx.doi.org/10.1097/00004424-199407000-00003.

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Lee, Sekwang, Sung-Bom Pyun, Kwan Woo Choi, and Woo-Suk Tae. "Shape and Volumetric Differences in the Corpus Callosum between Patients with Major Depressive Disorder and Healthy Controls." Psychiatry Investigation 17, no. 9 (2020): 941–50. http://dx.doi.org/10.30773/pi.2020.0157.

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Objective This study aimed to investigate the morphometric differences in the corpus callosum between patients with major depressive disorder (MDD) and healthy controls and analyze their relationship to gray matter changes.Methods Twenty female MDD patients and 21 healthy controls (HCs) were included in the study. To identify the difference in the regional gray matter concentration (GMC), VBM was performed with T1 magnetic resonance imaging. The shape analysis of the corpus callosum was processed. Diffusion tensor imaging (DTI) fiber-tracking was performed to identify the regional tract pathwa

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Oesch, Gabriela, A. Murat Maga, Seth D. Friedman, et al. "Geometric morphometrics reveal altered corpus callosum shape in pyridoxine-dependent epilepsy." Neurology 91, no. 1 (2018): e78-e86. http://dx.doi.org/10.1212/wnl.0000000000005748.

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ObjectiveTo evaluate the features and maturational changes in overall callosal shape in patients with pyridoxine-dependent epilepsy (PDE).MethodsMeasurements were conducted through landmark-based geometric morphometrics applied on cerebral MRIs of patients with PDE and age-matched control subjects. The outline of the corpus callosum was manually traced in the midsagittal plane. Three hundred semi-landmarks along the outline were collected and underwent statistical generalized Procrustes analysis. An allometric regression was applied to evaluate the callosal shape due to growth over time.Result

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Baykara, Sema, Murat Baykara, and Murad Atmaca. "Statistical shape analysis of Corpus Callosum in vaginismus." Archives of Psychiatry and Psychotherapy 25, no. 2 (2023): 37–44. http://dx.doi.org/10.12740/app/155218.

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Aim of the studyVaginismus is the presence spasm of the muscles in the vagina in the absence of any disease. Neurological diseases can cause degenerative changes in brain structures such as the corpus callosum (CC). The aim of this study is to evaluate the corpus callosum of patients with vaginismus with statistical shape analysis (SSA) using magnetic resonance imaging (MRI) images and compare it with healthy controls.Subject or material and methodsTen female patients with vaginismus and healthy individuals who met the study criteria, were equal in number and age were selected as the control.

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Book chapters on the topic "Corpus callosum shape"

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Türk, Yaşar. "Statistical Shape Analysis of Corpus Callosum." In The Corpus Callosum. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-38114-0_41.

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Herrera, W. G., M. Bento, and L. Rittner. "Corpus Callosum Shape Signature for Segmentation Evaluation." In XXVI Brazilian Congress on Biomedical Engineering. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-2517-5_22.

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Golland, Polina, W. Eric L. Grimson, and Ron Kikinis. "Statistical Shape Analysis Using Fixed Topology Skeletons: Corpus Callosum Study." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48714-x_33.

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Turgut, Umut Orcun, and Didem Gokcay. "Shape Preservation Based on Gaussian Radial Basis Function Interpolation on Human Corpus Callosum." In Spectral and Shape Analysis in Medical Imaging. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-51237-2_10.

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Dubb, Abraham, Brian Avants, Ruben Gur, and James Gee. "Shape Characterization of the Corpus Callosum in Schizophrenia Using Template Deformation." In Medical Image Computing and Computer-Assisted Intervention — MICCAI 2002. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45787-9_48.

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Jhaveri, Miral D., Karen L. Salzman, Jeffrey S. Ross, Kevin R. Moore, Anne G. Osborn, and Chang Yueh Ho. "Abnormal Shape/Configuration of Corpus Callosum." In Expertddx: Brain and Spine. Elsevier, 2018. http://dx.doi.org/10.1016/b978-0-323-44308-1.50106-9.

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Bhalerao, Gaurav Vivek, and Niranjana Sampathila. "Classification of Brain MR Images Using Corpus Callosum Shape Measurements." In Medical Imaging. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-0571-6.ch060.

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The corpus callosum is the largest white matter structure in the brain, which connects the two cerebral hemispheres and facilitates the inter-hemispheric communication. Abnormal anatomy of corpus callosum has been revealed for various brain related diseases. Being an important biomarker, Magnetic Resonance Imaging of the brain followed by corpus callosum segmentation and feature extraction has found to be important for the diagnosis of many neurological diseases. This paper focuses on classification of T1-weighted mid-sagittal MR images of brain for dementia patients. The corpus callosum is se

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Elnakib, Ahmed, Manuel F. Casanova, Georgy Gimel’farb, and Ayman El-Baz. "Autism Diagnostics by 3D Shape Analysis of the Corpus Callosum." In Machine Learning in Computer-Aided Diagnosis. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-4666-0059-1.ch015.

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The importance of accurate diagnostics of autism that severely affects personal behavior and communication skills cannot be overstated. Neuropathological studies have revealed an abnormal anatomy of the Corpus Callosum (CC) in autistic brains. This chapter proposes a new approach to quantitative analyses of three-dimensional (3D) Magnetic Resonance Images (MRI) of the brain that ensures a more accurate quantification of the anatomical differences between the CC of autistic and normal subjects. It consists of three main processing steps: (1) segmenting the CC from a given 3D MRI using the learn

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Elnakib, Ahmed, Manuel F. Casanova, Ahmed Soliman, Georgy Gimel'farb, and Ayman El-Baz. "Analysis of 3D Corpus Callosum Images in the Brains of Autistic Individuals." In Handbook of Research on Trends in the Diagnosis and Treatment of Chronic Conditions. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-8828-5.ch008.

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Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that is characterized by abnormalities in behavior and higher cognitive functions. The corpus callosum (CC) is the largest fiber bundle that connects the left and the right cerebral hemispheres of the human brain. Several studies have revealed an abnormal anatomy of the CC in the brains of autistic individuals that associates this neurodevelopmental condition with impaired communication between the hemispheres. In this chapter, we develop a framework to analyze the CC of autistic individuals in order to provide a diagnosti

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Damaskinou, Nikoleta. "Hemispheric Processing of Facial Emotion Recognition and Development in Children." In Clinical Applications of Pediatric Neuropsychology from Infancy to Adolescence. IGI Global, 2025. https://doi.org/10.4018/979-8-3693-9689-6.ch003.

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This chapter examines facial emotion recognition, a vital skill for social interaction and emotional development, from evolutionary, developmental, and neurological perspectives. It explores how children's ability to recognize emotions develops through social experiences, brain maturation, and lateralization. Key milestones, such as the shift from featural to holistic facial processing and sensitivity to emotional intensity, are discussed alongside insights into the right hemisphere's dominance in emotion recognition. The chapter also highlights sex differences, the role of the corpus callosum

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Conference papers on the topic "Corpus callosum shape"

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Silva, Suellen S., Joany S. Rodrigues, Paulo R. Julio, Simone Appenzeller, and Leticia Rittner. "Training a Vision Transformer Model on Shape Signatures for Quality Control of MRI Corpus Callosum Segmentations." In 2024 20th International Symposium on Medical Information Processing and Analysis (SIPAIM). IEEE, 2024. https://doi.org/10.1109/sipaim62974.2024.10783553.

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Farag, A., S. Elhabian, M. Abdelrahman, et al. "Shape modeling of the corpus callosum." In 2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2010). IEEE, 2010. http://dx.doi.org/10.1109/iembs.2010.5626169.

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Ayers, Brandon, Eileen Luders, Nicolas Cherbuin, and Shantanu H. Joshi. "Corpus callosum thickness estimation using elastic shape matching." In 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI 2015). IEEE, 2015. http://dx.doi.org/10.1109/isbi.2015.7164166.

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Shuyu, Li, Pu Fang, He Xiangqi, Deyu Li, and Jiang Tianzi. "Shape Analysis of the Corpus Callosum in Alzheimer's Disease." In 2007 1st International Conference on Bioinformatics and Biomedical Engineering. IEEE, 2007. http://dx.doi.org/10.1109/icbbe.2007.283.

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Elnakib, Ahmed, Ayman El-Baz, Manuel F. Casanova, and Andrew E. Switala. "Dyslexia Diagnostics by Centerline-Based Shape Analysis of the Corpus Callosum." In 2010 20th International Conference on Pattern Recognition (ICPR). IEEE, 2010. http://dx.doi.org/10.1109/icpr.2010.73.

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He, Qing, Ye Duan, Judith Miles, and Nicole Takahashi. "Statistical Shape Analysis of the Corpus Callosum in Subtypes of Autism." In 2007 IEEE 7th International Symposium on BioInformatics and BioEngineering. IEEE, 2007. http://dx.doi.org/10.1109/bibe.2007.4375694.

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Derraz, F., A. Taleb-Ahmed, L. Peyrodie, A. Pinti, A. Chikh, and F. Bereksi-Reguig. "Notice of Removal: Corpus callosum shape deformation analysis for multiple sclerosis." In 2010 International Conference on BioInformatics and BioEngineering (BIBE). IEEE, 2010. http://dx.doi.org/10.1109/bibe.2010.59.

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Elnakib, A., M. F. Casanova, G. Gimel'farb, A. E. Switala, and A. El-Baz. "Autism diagnostics by centerline-based shape analysis of the Corpus Callosum." In 2011 8th IEEE International Symposium on Biomedical Imaging (ISBI 2011). IEEE, 2011. http://dx.doi.org/10.1109/isbi.2011.5872766.

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Turgut, Umut Orcun, and Didem Gokcay. "Describing morphological changes of Corpus Callosum via shape grammar based approach." In 2015 Medical Technologies National Conference (TIPTEKNO). IEEE, 2015. http://dx.doi.org/10.1109/tiptekno.2015.7374603.

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He, Qing, Ye Duan, Xiaotian Yin, Xianfeng Gu, Kevin Karsch, and Judith Miles. "Shape analysis of corpus callosum in autism subtype using planar conformal mapping." In SPIE Medical Imaging, edited by Xiaoping P. Hu and Anne V. Clough. SPIE, 2009. http://dx.doi.org/10.1117/12.812285.

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