Abstract
In this study, a multistage segmentation technique is proposed that identifies cancerous cells in prostate tissue samples. The benign areas of the tissue are distinguished from the cancerous regions using the texture of glands. The texture is modeled based on wavelet packet features along with sample entropy values. In a multistage segmentation process, the mean-shift algorithm is applied on the pre-processed images to perform a coarse segmentation of the tissue. Wavelet packets are employed in the second stage to obtain fine details of the structured shape of glands. Finally, the texture of the gland is modeled by the sample entropy values, which identifies epithelial regions from stroma patches. Although there are three stages of the proposed algorithm, the computation is fast as wavelet packet features and sample entropy values perform robust modeling for the required regions of interest. A comparative analysis with other state-of-the-art texture segmentation techniques is presented and dice ratios are computed for the comparison. It has been observed that our algorithm not only outperforms other techniques, but, by introducing sample entropy features, identification of cancerous regions of tissues is achieved with 90% classification accuracy, which shows the robustness of the proposed algorithm.
Highlights
There are around 700,000 deaths from prostate cancer per year worldwide, and it is one of the top five cancers that cause fatality [1,2]
A major strength of our algorithm is that it does not result in holes, formed during segmentation of the lumen when only texture is used as a cue, because of its use of prior knowledge about gland formation and sequentially connecting epithelial nuclei on the glandular boundary
The classification criterion is based on the sample entropy and wavelet packet features for a patch
Summary
There are around 700,000 deaths from prostate cancer per year worldwide, and it is one of the top five cancers that cause fatality [1,2]. Screening is aimed at finding polyps, a collection of tiny cells on the prostate surface that are either benign or malignant. Benign cells are not harmful, but malignant cells may develop into cancer in less than five years [5]. It is known that manual screening increases the burden on physicians, and they spend most of their time looking into benign tissues [6]. Automation in the diagnosis, especially in benign cases, will reduce the burden on pathologists, who will only spend time in examining cancer tissues and can focus more on difficult cases. It is said that histopathology is the profession that has not changed much over the last 100 years [10]
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