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An automated method for segmenting white matter lesions through multi-level morphometric feature classification with application to lupus
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نویسنده
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scully m. ,anderson b. ,lane t. ,gasparovic c. ,magnotta v. ,sibbitt w. ,roldan c. ,kikinis r. ,bockholt h.j.
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منبع
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frontiers in human neuroscience - 2010 - دوره : 4 - شماره : 0
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چکیده
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We demonstrate an automated,multi-level method to segment white matter brain lesions and apply it to lupus. the method makes use of local morphometric features based on multiple mr sequences,including t1-weighted,t2-weighted,and fl uid attenuated inversion recovery. after preprocessing,including co-registration,brain extraction,bias correction,and intensity standardization,49 features are calculated for each brain voxel based on local morphometry. at each level of segmentation a supervised classifi er takes advantage of a different subset of the features to conservatively segment lesion voxels,passing on more diffi cult voxels to the next classifi er. this multi-level approach allows for a fast lesion classifi cation method with tunable trade-offs between sensitivity and specifi city producing accuracy comparable to a human rater. © 2010 scully,anderson,lane,gasparovic,magnotta,sibbitt,roldan,kikinis and bockholt.
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کلیدواژه
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Classifi cation; Lesion; Lupus; Machine learning; Method; Segmentation; Support vector machine
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آدرس
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the mind research network,albuquerque,nm,united states,department of computer science,the university of new mexico,albuquerque,nm,united states,advanced biomedical informatics group llc,iowa city,ia, United States, department of computer science,the university of new mexico,albuquerque,nm, United States, department of computer science,the university of new mexico,albuquerque,nm, United States, the mind research network,albuquerque,nm,united states,department of psychology,the university of new mexico,albuquerque,nm, United States, radiology department,carver school of medicine,the university of iowa,iowa city,ia, United States, rheumatology,department of internal medicine,school of medicine,the university of new mexico,albuquerque,nm, United States, cardiology,department of internal medicine,school of medicine,the university of new mexico,albuquerque,nm, United States, surgical planning laboratory,brigham and women's hospital,harvard school of medicine,boston,ma, United States, the mind research network,albuquerque,nm,united states,advanced biomedical informatics group llc,iowa city,ia, United States
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Authors
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