title: Pattern-recognition system, designed on GPU, for discriminating between injured normal and pathological knee cartilage.
abstract: The aim was to design a pattern-recognition (PR) system for discriminating between normal and pathological knee articular cartilage of the medial femoral (MFC) and tibial condyles (MTC). The data set comprised segmented regions of interest (ROIs) from coronal and sagittal 3-T magnetic resonance images of the MFC and MTC cartilage of young patients, 28 with abnormality-free knee and 16 with pathological findings. The PR system was designed employing the probabilistic neural network classifier, textural features from the segmented ROIs and the leave-one-out evaluation method, while the PR system's precision to "unseen" data was assessed by employing the external cross-validation method. Optimal system design was accomplished on a consumer graphics processing unit (GPU) using Compute Unified Device Architecture parallel programming. PR system design on the GPU required about 3.5 min against 15 h on a CPU-based system. Highest classification accuracies for the MFC and MTC cartilages were 93.2% and 95.5%, and accuracies to "unseen" data were 89% and 86%, respectively. The proposed PR system is housed in a PC, equipped with a consumer GPU, and it may be easily retrained when new verified data are incorporated in its repository and may be of value as a second-opinion tool in a clinical environment.
authors: Department of Medical Instruments Technology, Technological Educational Institute of Athens, Ag. Spyridonos, Egaleo, 12210 Athens, Greece.
authors: Spiros
authors: S
authors: Kostopoulos
authors: Konstantinos
authors: K
authors: Sidiropoulos
authors: Dimitris
authors: D
authors: Glotsos
authors: Emmanouil
authors: E
authors: Athanasiadis
authors: Konstantina
authors: K
authors: Boutsikou
authors: Eleftherios
authors: E
authors: Lavdas
authors: Georgia
authors: G
authors: Oikonomou
authors: Ioannis V
authors: IV
authors: Fezoulidis
authors: Marianna
authors: M
authors: Vlychou
authors: Michael
authors: M
authors: Hantes
authors: Dionisis
authors: D
authors: Cavouras
mesh_terms: D000328:Adult; D000465:Algorithms; D003196:Computer Graphics / Q000295:instrumentation*; D003937:Diagnosis, Differential; D004867:Equipment Design; D019544:Equipment Failure Analysis; D005260:Female; D050724:Fractures, Cartilage / Q000473:pathology*; D006801:Humans; D007089:Image Enhancement / Q000295:instrumentation / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000295:instrumentation* / Q000379:methods*; D007718:Knee Injuries / Q000473:pathology*; D008297:Male; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*; D055815:Young Adult