A Multi-atlas Approach to Region of Interest Detection for Medical Image Classification

  • Hongzhi WangEmail author
  • Mehdi Moradi
  • Yaniv Gur
  • Prasanth Prasanna
  • Tanveer Syeda-Mahmood
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10435)


A common approach for image classification is based on image feature extraction and supervised discriminative learning. For medical image classification problems where discriminative image features are spatially distributed around certain anatomical structures, localizing the region of interest (ROI) essential for the classification task is a key to success. To address this problem, we develop a multi-atlas label fusion technique for automatic ROI detection. Given a set of training images with class labels, our method infers voxel-wise scores for each image showing how discriminative each voxel is for categorizing the image. We applied our method in a 2D cardiac CT body part classification application and show the effectiveness of the detected ROIs.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Hongzhi Wang
    • 1
    Email author
  • Mehdi Moradi
    • 1
  • Yaniv Gur
    • 1
  • Prasanth Prasanna
    • 1
  • Tanveer Syeda-Mahmood
    • 1
  1. 1.IBM Almaden Research CenterSan JoseUSA

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