Advances in experimental medicine and biology
Jan 1, 2020
Antibody V domain clustering is of paramount importance to a repertoire of immunology-related areas. Although several approaches have been proposed for antibody clustering, still no consensus has been reached. Numerous attempts use information from g...
Advances in experimental medicine and biology
Jan 1, 2020
Advancements in musculoskeletal analysis have been achieved by adopting deep learning technology in image recognition and analysis. Unlike musculoskeletal modeling based on computational anatomy, deep learning-based methods can obtain muscle informat...
Advances in experimental medicine and biology
Jan 1, 2020
The skin is the largest organ of our body. Skin disease abnormalities which occur within the skin layers are difficult to examine visually and often require biopsies to make a confirmation on a suspected condition. Such invasive methods are not well-...
Advances in experimental medicine and biology
Jan 1, 2020
This chapter focuses on modern deep learning techniques that are proposed for automatically recognizing and segmenting multiple organ regions on three-dimensional (3D) computed tomography (CT) images. CT images are widely used to visualize 3D anatomi...
Advances in experimental medicine and biology
Jan 1, 2020
Early detection of glaucoma is important to slow down progression of the disease and to prevent total vision loss. Retinal fundus photography is frequently obtained for various eye disease diagnosis and record and is a suitable screening exam for its...
Advances in experimental medicine and biology
Jan 1, 2020
At medical checkups or mass screenings, the fundus examination is effective for early detection of systemic hypertension, arteriosclerosis, diabetic retinopathy, etc. In most cases, ophthalmologists and physicians grade retinal images by the conditio...
Advances in experimental medicine and biology
Jan 1, 2020
This chapter proposes a method to detect metastatic liver cancer from X-ray CT images using a convolutional neural network (CNN). The proposed method generates various lesion images by the combination of three kinds of generation methods: (1) synthes...
Advances in experimental medicine and biology
Jan 1, 2020
For computer-aided diagnosis (CAD), detection, segmentation, and classification from medical imagery are three key components to efficiently assist physicians for accurate diagnosis. In this chapter, a completely integrated CAD system based on deep l...
Advances in experimental medicine and biology
Jan 1, 2020
Image-based computer-aided diagnosis (CAD) algorithms by the use of convolutional neural network (CNN) which do not require the image-feature extractor are powerful compared with conventional feature-based CAD algorithms which require the image-featu...
Advances in experimental medicine and biology
Jan 1, 2020
Medical images have been widely used in clinics, providing visual representations of under-skin tissues in human body. By applying different imaging protocols, diverse modalities of medical images with unique characteristics of visualization can be p...