TISSUE CHARACTERIZATION BASED ON MACHINE LEARNING IN MEDICAL IMAGING

TISSUE CHARACTERIZATION BASED ON MACHINE LEARNING IN MEDICAL IMAGING

Tissue is characterized using machine-learnt classification. The prognosis, diagnosis or evidence in the form of a similar case is found by machine-learnt classification from features extracted from frames of medical scan data. The texture features for tissue characterization may be learned using de...

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Bibliographische Detailangaben
Hauptverfasser: Odry, Benjamin L, Kamel, Ihab, Liu, David, Zhou, Shaohua Kevin, Kiraly, Atilla Peter, Grimm, Robert, Kiefer, Berthold, Pan, Li
Format: Patent
Sprache:eng ; fre ; ger
Schlagworte:
HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA
INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS
PHYSICS
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Beschreibung
Zusammenfassung:Tissue is characterized using machine-learnt classification. The prognosis, diagnosis or evidence in the form of a similar case is found by machine-learnt classification from features extracted from frames of medical scan data. The texture features for tissue characterization may be learned using deep learning. Using the features, therapy response is predicted from magnetic resonance functional measures before and after treatment in one example. Using the machine-learnt classification, the number of measures after treatment may be reduced as compared to RECIST for predicting the outcome of the treatment, allowing earlier termination or alteration of the therapy.