Patch-Based Abnormality Maps for Improved Deep Learning-Based Classification of Huntington’s Disease
| العنوان: | Patch-Based Abnormality Maps for Improved Deep Learning-Based Classification of Huntington’s Disease |
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| المؤلفون: | Rémi Giraud, Ipek Oguz, Kilian Hett, Jeffrey D. Long, Hans J. Johnson, Jane S. Paulsen |
| المصدر: | Med Image Comput Comput Assist Interv Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 ISBN: 9783030597276 MICCAI (7) |
| سنة النشر: | 2020 |
| مصطلحات موضوعية: | Training set, Standard test image, Computer science, business.industry, Deep learning, education, Pattern recognition, Article, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Artificial intelligence, Abnormality, business, 030217 neurology & neurosurgery |
| الوصف: | Deep learning techniques have demonstrated state-of-the-art performances in many medical imaging applications. These methods can efficiently learn specific patterns. An alternative approach to deep learning is patch-based grading methods, which aim to detect local similarities and differences between groups of subjects. This latter approach usually requires less training data compared to deep learning techniques. In this work, we propose two major contributions: first, we combine patch-based and deep learning methods. Second, we propose to extend the patch-based grading method to a new patch-based abnormality metric. Our method enables us to detect localized structural abnormalities in a test image by comparison to a template library consisting of images from a variety of healthy controls. We evaluate our method by comparing classification performance using different sets of features and models. Our experiments show that our novel patch-based abnormality metric increases deep learning performance from 91.3% to 95.8% of accuracy compared to standard deep learning approaches based on the MRI intensity. |
| اللغة: | English |
| ردمك: | 978-3-030-59727-6 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ec472d02588bec53f5679a0d002a4b9a https://europepmc.org/articles/PMC8643359/ |
| Rights: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....ec472d02588bec53f5679a0d002a4b9a |
| قاعدة البيانات: | OpenAIRE |
| ردمك: | 9783030597276 |
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