Simultaneous detection and classification of breast masses in digital mammograms via a deep learning YOLO-based CAD system.

Background And Objective: Automatic detection and classification of the masses in mammograms are still a big challenge and play a crucial role to assist radiologists for accurate diagnosis. In this paper, we propose a novel Computer-Aided Diagnosis (CAD) system based on one of the regional deep learning techniques, a ROI-based Convolutional Neural Network (CNN) which is called You Only Look Once (YOLO). Although most previous studies only deal with classification of masses, our proposed YOLO-based CAD system can handle detection and classification simultaneously in one framework.

Detection and classification of the breast abnormalities in digital mammograms via regional Convolutional Neural Network.

Automatic detection and classification of the masses in mammograms are still a big challenge and play a crucial role to assist radiologists for accurate diagnosis. In this paper, we propose a novel computer-aided diagnose (CAD) system based on one of the regional deep learning techniques: a ROI-based Convolutional Neural Network (CNN) which is called You Only Look Once (YOLO). Our proposed YOLO-based CAD system contains four main stages: mammograms preprocessing, feature extraction utilizing multi convolutional deep layers, mass detection with confidence model, and finally mass classification using fully connected neural network (FC-NN).

Non-local means filter denoising for DEXA images.

Dual high and low energy images of Dual Energy X-ray Absorptiometry (DEXA) suffer from noises due to the use of weak amount of X-rays. Denoising these DEXA images could be a key process to enhance and improve a Bone Mineral Density (BMD) map which is derived from a pair of high and low energy images. This could further improve the accuracy of diagnosis of bone fractures, osteoporosis, and etc.

Development of skeletal muscle and expression of myogenic regulatory factors during embryonic development in Jinding ducks (Anas platyrhynchos domestica).

The important roles of myogenic regulatory factors (MRF) in mammalian skeletal myogenesis have been well studied, but few equivalent studies have been performed in poultry. The expression pattern of MRF during the embryonic development of skeletal muscle in ducks remains unknown. In this study, we identified Myf5, Myf6, MyoD, and myogenin genes in Jinding ducks (Anas platyrhynchos domestica) and quantified their expression levels in breast muscle (BM) and leg muscle (LM) at embryonic d 13, 17, 21, 25, and 27 by real-time reverse-transcription PCR.

Nasal T/NK cell lymphoma: a clinico pathologic study of 30 west Chinese patients with special reference to proliferation and apoptosis.

Midfacial T-cell lymphomas are more prevalent in Asia than in Europe or North America. Clinically, these lymphomas are noted as one major differential diagnosis in the malignant midline granuloma syndrome. During the past years, the group of nasal T/NK cell lymphomas has been recognized that is frequently associated with EBV-infection.