The detection of prostate cancer based on ultrasound RF signal - Xiao, Tianlei; Shen, Weiwei; Wang, Qingming; Wu, Guoqing; Yu, Jinhua; Cui, Ligang (Frontiers in Oncology, 2022)
This paper proposes a novel and accurate method for detecting prostate cancer based on the ultrasound radiofrequency (RF) signal. The diagnosis of prostate cancer has been a challenging task. Compared to traditional diagnosis methods, RF signal is not only non-invasive but also rich in microscopic lesion information. Our approach is based on low-dimensional features in frequency domain and high-throughput features in spatial domain. The whole process could be divided into two parts: first, we calculate three feature maps from the ultrasound original RF signal, and 1050 radiomics features are extracted from the three feature maps; second, we extracted 37 spectral features from the normalized frequency spectrum after Fourier transform. We use Lasso regression as the method for feature select, meanwhile, we use support vector machine (SVM) for classification 10-fold cross-validation for examining the classification performance of the SVM An AUC (area under receiver operating characteristics curve) of 0.84 was obtained on 71 subjects.