Combining classifiers for bone fracture detection in X-ray images

In medical applications, sensitivity in detecting medical problems and accuracy of detection are often in conflict. A single classifier usually cannot achieve both high sensitivity and accuracy at the same time. Methods of combining classifiers have been proposed in the literature. This paper presents a study of probabilistic combination methods applied to the detection of bone fractures in x-ray images. Test results show that the effectiveness of a method in improving both accuracy and sensitivity depends on the nature of the method as well as the proportion of positive samples.

• Type: Conference
• Year: 2005
• Where: ICIP
• Authors: Vineta Lai Fun Lum, Wee Kheng Leow, Ying Chen, Tet Sen Howe, Meng Ai Png
• Keywords: Bone Fractures, ICIP 2005, Image Processing, Probabilistic Combination Methods, Single Classifier