Quantitation of T2 lesion load in multiple sclerosis with magnetic resonance imaging: A pilot study of a probabilistic neural network approach

To quantitate multiple sclerosis (MS) lesions in the brain by using computerized techniques. MS lesions from five patients were quantitated with magnetic resonance (MR) imaging by using three approaches: a probabilistic neural network (PNN) approach, a semiautomated method that uses a bifeature spac...

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Veröffentlicht in:Academic radiology 1997-06, Vol.4 (6), p.431-437
Hauptverfasser: Raff, Ulrich, Vargas, Patricio F., Rojas, Gonzalo M., Scherzinger, Ann L., Simon, Jack H.
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container_end_page 437
container_issue 6
container_start_page 431
container_title Academic radiology
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creator Raff, Ulrich
Vargas, Patricio F.
Rojas, Gonzalo M.
Scherzinger, Ann L.
Simon, Jack H.
description To quantitate multiple sclerosis (MS) lesions in the brain by using computerized techniques. MS lesions from five patients were quantitated with magnetic resonance (MR) imaging by using three approaches: a probabilistic neural network (PNN) approach, a semiautomated method that uses a bifeature space approach with operator intervention at each section, and the “gold standard” of manual outlining of lesions. Each patient underwent two MR studies in 1 day. The PNN approach allows reasonable quantitation of large data sets with minimal operator input. The mean intraobserver error for the PNN approach was competitive with the more time-consuming bifeature space approach (5.2% vs 4.4%, respectively). On average, both computer-assisted methods performed better than the manual method (mean intra-observer error, 10.1%). The agreement between the two computerized quantitation approaches was good. The number of interactive steps was substantially reduced with the PNN technique, leading to minimal operator intervention time.
doi_str_mv 10.1016/S1076-6332(97)80051-7
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source MEDLINE; Elsevier ScienceDirect Journals
subjects Brain - pathology
Computers, neural network
Humans
magnetic resonance (MR), volume measurement
Magnetic Resonance Imaging
Multiple Sclerosis - pathology
Neural Networks (Computer)
Observer Variation
Pilot Projects
sclerosis, multiple
title Quantitation of T2 lesion load in multiple sclerosis with magnetic resonance imaging: A pilot study of a probabilistic neural network approach
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