Conference Paper

Lecture Notes in Computer Science

DOI: 10.1007/978-3-642-23944-1_12 Conference: Prostate Cancer Imaging. Image Analysis and Image-Guided Interventions - International Workshop, Held in Conjunction with MICCAI 2011, Toronto, Canada, September 22, 2011. Proceedings
Source: DBLP


Prostate cancer is one of the most frequently diagnosed neoplasy and its presence can only be confirmed by biopsy. Due to the high number of false positives, Computer Aided Detection (CAD) systems can be used to reduce the number of cores requested for an accurate diagnosis. This work proposes a CAD procedure for cancer detection in Ultrasound images based on a learning scheme which exploits a novel semi-supervised learning (SSL) algorithm for reducing data collection effort and avoiding collected data wasting. The ground truth database comprises the RF-signals acquired during biopsies and the corresponding tissue samples histopathological outcome. A comparison to a state-of-art CAD scheme based on supervised learning demonstrates the effectiveness of the proposed SSL procedure at enhancing CAD performance. Experiments on ground truth images from biopsy findings show that the proposed CAD scheme is effective at improving the efficiency of the biopsy protocol.

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