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Assessment of Computational Visual Attention Models on Medical Images


Conference Paper


Visual attention plays a major role in our lives. Our very perception (which very much decides our survival) depends on it - like perceiving a predator while walking through a forest, perceiving a fast car coming from the front on a busy road or even spotting our favorite color out of the many colors. In Medical Imaging, where medical experts have to take major clinical decisions based on the examination of images of various kinds (CT, MRI etc), visual attention plays a pivotal role. It makes the medical experts fixate on any abnormal behavior exhibited in the medical image and helps in speedy diagnosis. Many previous works (see the paper for details) have exhibited this important fact and the model proposed by Nodine and Kundel highlights the important role of visual attention in medical image diagnosis. Visual attention involves two components - Bottom-Up and Top-Down.In the present work, we examine a number of established computational models of visual attention in the context of chest X-rays (infected with Pneumoconiosis) and retinal images (having hard exudates). The fundamental motivation is to try to understand the applicability of visual attention models in the context of different types of abnormalities. Our assessment of four popular visual attention models, is extensive and shows that they are able to pick up abnormal features reasonably well. We compare the models towards detecting subtle abnormalities and high-contrast lesions. Although significant scope of improvements exists especially in picking up more subtle abnormalities and getting more selective towards picking up more abnormalities and less normal structures, the presented assessment shows that visual attention indeed shows a promise for inclusion in the main field of medical image analysis

Author(s): Varun Jampani and Ujjwal and Jayanthi Sivaswamy and Vivek Vaidya
Book Title: Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing
Pages: 80:1--80:8
Year: 2012
Month: December
Publisher: ACM

Department(s): Perceiving Systems
Bibtex Type: Conference Paper (conference)
Paper Type: Conference

Address: Mumbai, India
URL: http://doi.acm.org/10.1145/2425333.2425413

Links: url


  title = {Assessment of Computational Visual Attention Models on Medical Images},
  author = {Jampani, Varun and Ujjwal and Sivaswamy, Jayanthi and Vaidya, Vivek},
  booktitle = {Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing},
  pages = {80:1--80:8},
  publisher = {ACM},
  address = {Mumbai, India},
  month = dec,
  year = {2012},
  url = {http://doi.acm.org/10.1145/2425333.2425413},
  month_numeric = {12}