Segmentation of Glomeruli Within Trichrome Images Using Deep Learning
نویسندگان
چکیده
منابع مشابه
Using Deep Learning for Segmentation and Counting within Microscopy Data
Cell counting is a ubiquitous, yet tedious task that would greatly benefit from automation. From basic biological questions to clinical trials, cell counts provide key quantitative feedback that drive research. Unfortunately, cell counting is most commonly a manual task and can be timeintensive. The task is made even more difficult due to overlapping cells, existence of multiple focal planes, a...
متن کاملEarly detection of MS in fMRI images using deep learning techniques
Introduction & Objective:MS is a disease of the central nervous system in which the body makes a defensive attack on its tissues. The disease can affect the brain and spinal cord, causing a wide range of potential symptoms, including balance, movement and vision problems. MRI and fMRI images are a very important tool in the diagnosis and treatment of MS. The aim of this study was to provide...
متن کاملSegmentation of the Left Atrial Appendage in the Echocardiographic Images of the Heart Using a Deep Neural Network
Introduction: Cardiovascular diseases are one of the leading causes of mortality in today’s industrial world. Occlusion of left atrial appendage (LAA) using the manufactured devices is a growing trend. The objective of this study was to develop a computer-aided diagnosis system for the identification of LAA in echocardiographic images. Method: The data used in this descriptive analytical study ...
متن کاملMyocardial fibrosis delineation in late gadolinium enhancement images of Hypertrophic Cardiomyopathy patients using deep learning methods
Introduction: Accurate delineation of myocardial fibrosis in Late Gadolinium Enhancement on Cardiac Magnetic Resonance (LGE-CMR) has a crucial role in the assessment and risk stratification of HCM patients. As this is time-consuming and requires expertise, automation can be essential in accelerating this process. This study aims to use Unet-based deep learning methods to automate the mentioned ...
متن کاملFully automated, deep learning segmentation of oxygen-induced retinopathy images.
Oxygen-induced retinopathy (OIR) is a widely used model to study ischemia-driven neovascularization (NV) in the retina and to serve in proof-of-concept studies in evaluating antiangiogenic drugs for ocular, as well as nonocular, diseases. The primary parameters that are analyzed in this mouse model include the percentage of retina with vaso-obliteration (VO) and NV areas. However, quantificatio...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Kidney International Reports
سال: 2019
ISSN: 2468-0249
DOI: 10.1016/j.ekir.2019.04.008