IEEE journal of biomedical and health informatics
Jun 17, 2019
Many classical machine learning techniques have been used to explore Alzheimer's disease (AD), evolving from image decomposition techniques such as principal component analysis toward higher complexity, non-linear decomposition algorithms. With the a...
The use of artificial intelligence in medicine is currently an issue of great interest, especially with regard to the diagnostic or predictive analysis of medical data. In order to achieve the regional medical and public health data analysis through ...
Artificial intelligence (AI) has been present in some guise within the field of radiology for over 50 years. The first studies investigating computer-aided diagnosis in thoracic radiology date back to the 1960s, and in the subsequent years, the main ...
Various machine learning techniques have been developed for keratoconus detection and refractive surgery screening. These techniques utilize inputs from a range of corneal imaging devices and are built with automated decision trees, support vector ma...
Wart disease (WD) is a skin illness on the human body which is caused by the human papillomavirus (HPV). This study mainly concentrates on common and plantar warts. There are various treatment methods for this disease, including the popular immunothe...
Computer methods and programs in biomedicine
Jun 6, 2019
BACKGROUND AND OBJECTIVE: Chest X-ray (CXR) is one of the most used imaging techniques for detection and diagnosis of pulmonary diseases. A critical component in any computer-aided system, for either detection or diagnosis in digital CXR, is the auto...
The successful early diagnosis of brain tumors plays a major role in improving the treatment outcomes and thus improving patient survival. Manually evaluating the numerous magnetic resonance imaging (MRI) images produced routinely in the clinic is a ...
INTRODUCTION: Epileptologists could benefit from a diagnosis support system that automatically detects seizures because visual inspection of long-term electroencephalograms (EEGs) is extremely time-consuming. However, the diversity of seizures among ...
IMPORTANCE: Deep learning has the potential to augment clinician performance in medical imaging interpretation and reduce time to diagnosis through automated segmentation. Few studies to date have explored this topic.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jun 1, 2019
Extraction or segmentation of organ vessels is an important task for surgical planning and computer-aided diagnoses. This is a challenging task due to the extremely small size of the vessel structure, low SNR, and varying contrast in medical image da...