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Rapid image stitching and computer-aided detection for multipass automated breast ultrasound

Authors :
Kuang-Che Chang-Chien
Jeon-Hor Chen
Etsuo Takada
Chiun-Sheng Huang
Yi-Hong Chou
Ruey-Feng Chang
Chen-Ming Kuo
Source :
Medical Physics. 37:2063-2073
Publication Year :
2010
Publisher :
Wiley, 2010.

Abstract

Purpose: Breast ultrasound(US) is recently becoming more and more popular for detecting breast lesions. However, screening results in hundreds of USimages for each subject. This magnitude of images can lead to fatigue in radiologist, causing failure in the detection of lesions of a subtle nature. In this study, an image stitching technique is proposed for combining multipass images of the whole breast into a series of full-view images, and a fully automatic screening system that works off these images is also presented. Methods: Using the registration technique based on the simple sum of absolute block-mean difference (SBMD) measure, three-pass images were merged into full-view USimages. An automatic screening system was then developed for detecting tumors from these full-view images. The preprocessing step was used to reduce the tumor detection time of the system and to improve image quality. The gray-level slicing method was then used to divide images into numerous regions. Finally, seven computerized features—darkness, uniformity, width-height ratio, area size, nonpersistence, coronal area size, and region continuity—were defined and used to determine whether or not each region was a part of a tumor. Results: In the experiment, there was a total of 25 experimental cases with 26 lesions, and each case was composed of 252 images (three passes, 84 images/pass). The processing time of the proposed stitching procedure for each case was within 30 s with a Pentium IV 2.0 processor, and the detection sensitivity of the proposed CADsystem was 92.3% with 1.76 false positives per case. Conclusions: The proposed automatic screening system can be applied to the whole breast images stitched together via SBMD-based registration in order to detect tumors.

Details

ISSN :
00942405
Volume :
37
Database :
OpenAIRE
Journal :
Medical Physics
Accession number :
edsair.doi...........7094a6a105effdc2567e1579be46b4d0
Full Text :
https://doi.org/10.1118/1.3377775