Absolute cosine-based SVM-RFE feature selection method for prostate histopathological grading.

OBJECTIVE: Feature selection (FS) methods are widely used in grading and diagnosing prostate histopathological images. In this context, FS is based on the texture features obtained from the lumen, nuclei, cytoplasm and stroma, all of which are important tissue components. However, it is difficult to represent the high-dimensional textures of these tissue components. To solve this problem, we propose a new FS method that enables the selection of features with minimal redundancy in the tissue components. METHODOLOGY: We categorise tissue images based on the texture of individual tissue components via the construction of a single classifier and also construct an ensemble learning model by merging the values obtained by each classifier. Another issue that arises is overfitting due to the high-dimensional texture of individual tissue components. We propose a new FS method, SVM-RFE(AC), that integrates a Support Vector Machine-Recursive Feature Elimination (SVM-RFE) embedded procedure with an absolute cosine (AC) filter method to prevent redundancy in the selected features of the SV-RFE and an unoptimised classifier in the AC. RESULTS: We conducted experiments on H&E histopathological prostate and colon cancer images with respect to three prostate classifications, namely benign vs. grade 3, benign vs. grade 4 and grade 3 vs. grade 4. The colon benchmark dataset requires a distinction between grades 1 and 2, which are the most difficult cases to distinguish in the colon domain. The results obtained by both the single and ensemble classification models (which uses the product rule as its merging method) confirm that the proposed SVM-RFE(AC) is superior to the other SVM and SVM-RFE-based methods. CONCLUSION: We developed an FS method based on SVM-RFE and AC and successfully showed that its use enabled the identification of the most crucial texture feature of each tissue component. Thus, it makes possible the distinction between multiple Gleason grades (e.g. grade 3 vs. grade 4) and its performance is far superior to other reported FS methods.

Sarcoid Myopathy Mimicking Polymyositis: A Case Report and Pool Analysis of the Literature Reviews.

A 59-year-old man presented with proximal myopathy, myalgia, and weight loss, with the initial markedly elevated serum creatine kinase at 11,000 U/L. Due to his refusal for muscle biopsy, he was initially treated as inflammatory myositis and responded well with the corticosteroids. However, he subsequently had a relapse of the symptoms with more extensive systemic involvement, i.e., hypercalcemia, lymphadenopathy and subcutaneous nodules. Finally, a biopsy of the thigh and subcutaneous nodule revealed non-caseating granulomatous inflammation, consistent with sarcoidosis. He responded well to the corticosteroids, and finally, azathioprine was added as a steroid-sparing agent. Including our series, there are 103 cases of symptomatic muscle involvement in sarcoidosis patients published in the English literature to date. Further pool analysis of the cases will be reported in this review.