Congratulations to Roland Kwitt, Stephen Aylward, and Kitware’s collaborators on their journal article that appears in the October issue of Medical Image Analysis (Current Impact Factor: 4.087).
The paper presents a novel method that helps inexperienced people find structures in the human body using Ultrasound. In this manner, novice Ultrasound operators can consistently carry-out critical assessments of internal organ damage, detect cancer, and assess response to treatments. Thereby, Ultrasound becomes a powerful tool in rural emergency situations, for low-income countries, and for in-home patient monitoring.
The work presented in this journal article is an extension of our MICCAI 2012 paper that first introduced our technique. This journal article contains a more extensive set of experiments, and it also proposes an alternative recognition strategy based on capturing the dynamics of Bag-of-Word histogram changes over time using kernel dynamic textures. This new technique is shown to be more robust to acquisition variations.
The selection process for the “Special Issue on MICCAI papers” is particularly competitive. After each MICCAI conference, the top scoring conference papers are invited to submit a related article to the Medical Image Analysis (MedIA) journal. From MICCAI 2012, 16 papers were invited to MedIA, and 11 passed their extensive review process. Considering that 781 papers were submitted to MICCAI 2012, being accepted for publication in the MICCAI special issue of MedIA reflects an acceptance rate of 1.4%.
We are particularly grateful for and would like to thank our collaborators Sharif Razzaque (InnerOptic) and Nuno Vasconcelos (SVCL, UCSD) for their outstanding support and contributions to this work.
This work was supported, in part, by NIH/NIBIB grant “In-field FAST procedure support and automation” (S. Aylward, 1R43EB016621) and NIH/NCI grant “A needle guidance system for hepatic tumor ablation that fuses real-time ultrasound” (S. Razzaque – InnerOptic, 2R44CA143234).