Real-Time Patient Table Removal in CT Images

As a routine tool for screening and examination, CT plays an important role in disease detection and diagnosis. Real-time table removal in CT images becomes a fundamental task to improve readability, interpretation and treatment planning. Meanwhile, it makes data management simple and benefits information sharing and communication in picture archiving and communication system. In this paper, we proposed an automated framework which utilized parallel programming to address this problem. Eight full-body CT images were collected and analyzed. Experimental results have shown that with parallel programming, the proposed framework can accelerate the patient table removal task up to three times faster when it was running on a personal computer with four-core central processing unit. Moreover, the segmentation accuracy reaches 99 % of Dice coefficient. The idea behind this approach refreshes many algorithms for real-time medical image processing without extra hardware spending.

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