MGB-Unet: An Improved Multiscale Unet with Bottleneck Transformer for Myositis Segmentation from Ultrasound Images.

Myositis is the inflammation of the muscles that can arise from various sources with diverse symptoms and require different treatments. For treatment to achieve optimal results, it is essential to obtain an accurate diagnosis promptly. This paper presents a new supervised segmentation architecture that can efficiently perform precise segmentation and classification of myositis from ultrasound images with few computational resources.

CAT-Seg: cascaded medical assistive tool integrating residual attention mechanisms and Squeeze-Net for 3D MRI biventricular segmentation.

Cardiac image segmentation is a critical step in the early detection of cardiovascular disease. The segmentation of the biventricular is a prerequisite for evaluating cardiac function in cardiac magnetic resonance imaging (CMRI). In this paper, a cascaded model CAT-Seg is proposed for segmentation of 3D-CMRI volumes.

Detection and quantification of perioperative heparin-like effects by rotational thromboelastometry in living-donor liver transplant recipients: A prospective observational study.

Background And Aims: Heparin-like effects (HLEs) can affect hemostasis during liver transplantation. The aim of this study was to assess the perioperative incidence and severity of HLE with rotational thromboelastometry (ROTEM) and activated partial thromboplastin time (aPTT).

Material And Methods: ROTEM and aPTT were measured intraoperatively and on postoperative days (POD) 1, 3, and 7.

Abnormality detection and intelligent severity assessment of human chest computed tomography scans using deep learning: a case study on SARS-COV-2 assessment.

Different respiratory infections cause abnormal symptoms in lung parenchyma that show in chest computed tomography. Since December 2019, the SARS-COV-2 virus, which is the causative agent of COVID-19, has invaded the world causing high numbers of infections and deaths. The infection with SARS-COV-2 virus shows an abnormality in lung parenchyma that can be effectively detected using Computed Tomography (CT) imaging.