Medical image segmentation using deep semantic-based methods: A review of techniques, applications and emerging trends
Semantic-based segmentation (Semseg) methods play an essential part in medical imaging
analysis to improve the diagnostic process. In Semseg technique, every pixel of an image is …
analysis to improve the diagnostic process. In Semseg technique, every pixel of an image is …
A systematic review of deep learning based image segmentation to detect polyp
Among the world's most common cancers, colorectal cancer is the third most severe form of
cancer. Early polyp detection reduces the risk of colorectal cancer, vital for effective …
cancer. Early polyp detection reduces the risk of colorectal cancer, vital for effective …
Plantorganelle Hunter is an effective deep-learning-based method for plant organelle phenotyping in electron microscopy
Accurate delineation of plant cell organelles from electron microscope images is essential
for understanding subcellular behaviour and function. Here we develop a deep-learning …
for understanding subcellular behaviour and function. Here we develop a deep-learning …
AI-enabled biosensing for rapid pathogen detection: From liquid food to agricultural water
Rapid pathogen detection in food and agricultural water is essential for ensuring food safety
and public health. However, complex and noisy environmental background matrices delay …
and public health. However, complex and noisy environmental background matrices delay …
IRUNet for medical image segmentation
F Hoorali, H Khosravi, B Moradi - Expert Systems with Applications, 2022 - Elsevier
In recent years, deep learning has been widely used to segment medical images and assist
physicians in better diagnosis and treatment of diseases. Anthrax is a serious infectious …
physicians in better diagnosis and treatment of diseases. Anthrax is a serious infectious …
Harnessing of artificial intelligence for the diagnosis and prevention of hospital-acquired infections: a systematic review
B Baddal, F Taner, D Uzun Ozsahin - Diagnostics, 2024 - mdpi.com
Healthcare-associated infections (HAIs) are the most common adverse events in healthcare
and constitute a major global public health concern. Surveillance represents the foundation …
and constitute a major global public health concern. Surveillance represents the foundation …
An automated in vitro wound healing microscopy image analysis approach utilizing U-net-based deep learning methodology
Background The assessment of in vitro wound healing images is critical for determining the
efficacy of the therapy-of-interest that may influence the wound healing process. Existing …
efficacy of the therapy-of-interest that may influence the wound healing process. Existing …
Hybrid Adam sewing training optimization enabled deep learning for brain tumor segmentation and classification using MRI images
ABSTRACT A brain tumour (BT) is a growth of tissue that is organised by a gradual
accumulation of anomalous cells, and it is significant to segment and classify the BT from …
accumulation of anomalous cells, and it is significant to segment and classify the BT from …
Investigating the Identification and Spatial Distribution Characteristics of Camellia oleifera Plantations Using High-Resolution Imagery
Y Li, E Yan, J Jiang, D Cao, D Mo - Remote Sensing, 2023 - mdpi.com
Camellia oleifera is a vital economic crop of southern China. Accurate mapping and
monitoring of Camellia oleifera plantations are essential for promoting sustainable …
monitoring of Camellia oleifera plantations are essential for promoting sustainable …
[HTML][HTML] 改进型Unet 网络在脑CT 图像出血区域识别与分割中的应用
正松周， 旭淼陈， 皞宇张， 红丽万， 杰祎赵… - Journal of Sichuan …, 2022 - ncbi.nlm.nih.gov
改进型Unet网络在脑CT图像出血区域识别与分割中的应用- PMC Back to Top Skip to main
content NIH NLM Logo Access keys NCBI Homepage MyNCBI Homepage Main Content Main …
content NIH NLM Logo Access keys NCBI Homepage MyNCBI Homepage Main Content Main …