While clinicians can accurately identify different types of heartbeats in electrocardiograms (ECGs) from different patients, researchers have had limited success in applying supervised machine learning to the same task. The problem is made challenging by the variety of tasks, interand intra-patient differences, an often severe class imbalance, and the high cost of getting cardiologists to label...

In recent years, many convolutional neural network (CNN)-based methods have been proposed to address the scene classification tasks of remote sensing images. Since number training samples in RS datasets is generally small, data augmentation often used expand set. It is, however, not appropriate when original keep label and change content image at same time. this study, (LA) presented fully util...

This study describes novel methods for supporting navigation and placement of electrodes during surgeries for deep brain stimulation (DBS). Critical to these procedures in neurosurgery is the localization and identification of different target structures along the electrode's trajectory in the brain such as the subthalamic nucleus (STN), and finding the best position for the stimulating electro...

Abstract Background Myopic maculopathy (MM) is one of the major causes visual impairment and irreversible blindness in eyes with pathologic myopia (PM). However, classification each type lesion associated MM has not been determined. Recently, a new system, known as ATN grading was proposed; it based on fundus photographs optical coherence tomography (OCT) images includes three variable componen...

Classification-based approaches for segmenting medical images commonly suffer from missing ground truth: often one has to resort to manual labelings by human experts, which may show considerable intra-rater and inter-rater variability. We experimentally evaluate several latent class and latent score models for tumor classification based on manual segmentations of different quality, using approx...

Adhesive small bowel obstruction (ASBO) is one of the most frequently encountered disorders in Emergency Surgery Departments worldwide without negligible hospital admission rates and social costs (1,2). Notwithstanding significant improvements in techniques and materials, intra-abdominal adhesions following abdominal surgery still represent a major unsolved and debated issue harbouring challeng...