Machine learning approaches in medical image analysis: from detection to diagnosis

TY - JOUR

T1 - Machine learning approaches in medical image analysis

T2 - from detection to diagnosis

AU - de Bruijne, Marleen

PY - 2016

Y1 - 2016

N2 - Machine learning approaches are increasingly successful in image-based diagnosis, disease prognosis, and risk assessment. This paper highlights new research directions and discusses three main challenges related to machine learning in medical imaging: coping with variation in imaging protocols, learning from weak labels, and interpretation and evaluation of results.

AB - Machine learning approaches are increasingly successful in image-based diagnosis, disease prognosis, and risk assessment. This paper highlights new research directions and discusses three main challenges related to machine learning in medical imaging: coping with variation in imaging protocols, learning from weak labels, and interpretation and evaluation of results.

KW - Classification

KW - Computer aided diagnosis

KW - Machine learning

KW - Transfer learning

UR - http://www.scopus.com/inward/record.url?scp=84982105864&partnerID=8YFLogxK

U2 - 10.1016/j.media.2016.06.032

DO - 10.1016/j.media.2016.06.032

M3 - Editorial

C2 - 27481324

AN - SCOPUS:84982105864

SN - 1361-8415

VL - 33

SP - 94

EP - 97

JO - Medical Image Analysis

JF - Medical Image Analysis

ER -