Work

Patch-Based Abnormality Maps for Improved Deep Learning-Based Classification of Huntington’s Disease

Year: 2020

Type: conference-paper

Source: Lecture notes in computer science

DOI: 10.1007/978-3-030-59728-3_62

Authors: Kilian Hett, Rémi Giraud, Hans Johnson, Jane S. Paulsen, Jeffrey D. Long, Ipek Oguz

Institutions: Vanderbilt University, Centre National de la Recherche Scientifique, Université de Bordeaux, Laboratoire de l'Intégration du Matériau au Système, Institut Polytechnique de Bordeaux, University of Iowa, University of Wisconsin–Madison

Language: English

Topic: Medical Image Segmentation Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

Funder: National Institute of Neurological Disorders and Stroke

Awards: Neurobiological Predictors of Huntington's Disease, Statistical disease modeling and clinimetrics to prepare for preventive trials in huntington disease, Preparing for preventive clinical trials in Huntington's disease, Statistical disease modeling and clinimetrics to prepare for preventive trials in huntington disease, : Clinical Outcomes in Aicardi Goutières Syndrome, Early detection of Huntington's Disease: Longitudinal analysis of basal ganglia and cortical thickness, Preparing for preventive clinical trials in Huntington's disease

OpenAlex ID: W3089884436

FWCI: 0.154

Cites: 18

Cited by: 3

Related to: 10