Discriminative MR Image Feature Analysis for Automatic Schizophrenia and Alzheimer’s Disease Classification
| العنوان: | Discriminative MR Image Feature Analysis for Automatic Schizophrenia and Alzheimer’s Disease Classification |
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| المؤلفون: | L.A. Teverovskiy, Simon W. Davis, Yanxi Liu, V. Andrew Stenger, Owen Carmichael, Ron Kikinis, Carolyn C. Meltzer, Cameron S. Carter, Martha E. Shenton, Oscar L. Lopez, Howard J. Aizenstein, James T. Becker |
| المصدر: | Medical Image Computing and Computer-Assisted Intervention – MICCAI 2004 ISBN: 9783540229766 MICCAI (1) |
| بيانات النشر: | Springer Berlin Heidelberg, 2004. |
| سنة النشر: | 2004 |
| مصطلحات موضوعية: | medicine.diagnostic_test, Computer science, business.industry, Schizophrenia (object-oriented programming), Image (category theory), Magnetic resonance imaging, Pattern recognition, Disease, medicine.disease, Cross-validation, Discriminative model, Feature (computer vision), Schizophrenia, medicine, Brain asymmetry, Computer vision, Artificial intelligence, Cognitive impairment, business |
| الوصف: | We construct a computational framework for automatic cen- tral nervous system (CNS) disease discrimination using high resolution Magnetic Resonance Images (MRI) of human brains. More than 3000 MR image features are extracted, forming a high dimensional coarse- to-fine hierarchical image description that quantifies brain asymmetry, texture and statistical properties in corresponding local regions of the brain. Discriminative image feature subspaces are computed, evaluated and selected automatically. Our initial experimental results show 100% and 90% separability between chronicle schizophrenia (SZ) and first episode SZ versus their respective matched controls. Under the same computational framework, we also find higher than 95% separability among Alzheimer's Disease, mild cognitive impairment patients, and their matched controls. An average of 88% classification success rate is achieved using leave-one-out cross validation on five different well-chosen patient-control image sets of sizes from 15 to 27 subjects per disease class. |
| ردمك: | 978-3-540-22976-6 |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_________::afb18e5e4d7fd6e2c3f768d94acf00f8Test https://doi.org/10.1007/978-3-540-30135-6_48Test |
| حقوق: | OPEN |
| رقم الانضمام: | edsair.doi...........afb18e5e4d7fd6e2c3f768d94acf00f8 |
| قاعدة البيانات: | OpenAIRE |
| ردمك: | 9783540229766 |
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