AI in medical imaging informatics: current challenges and future directions
This paper reviews state-of-the-art research solutions across the spectrum of medical
imaging informatics, discusses clinical translation, and provides future directions for …
imaging informatics, discusses clinical translation, and provides future directions for …
Recent trends and advances in fundus image analysis: A review
Automated retinal image analysis holds prime significance in the accurate diagnosis of
various critical eye diseases that include diabetic retinopathy (DR), age-related macular …
various critical eye diseases that include diabetic retinopathy (DR), age-related macular …
Deep learning of the retina enables phenome-and genome-wide analyses of the microvasculature
Background: The microvasculature, the smallest blood vessels in the body, has key roles in
maintenance of organ health and tumorigenesis. The retinal fundus is a window for human …
maintenance of organ health and tumorigenesis. The retinal fundus is a window for human …
A deep learning approach for liver and tumor segmentation in CT images using ResUNet
According to the most recent estimates from global cancer statistics for 2020, liver cancer is
the ninth most common cancer in women. Segmenting the liver is difficult, and segmenting …
the ninth most common cancer in women. Segmenting the liver is difficult, and segmenting …
Review of semantic segmentation of medical images using modified architectures of UNET
M Krithika Alias AnbuDevi, K Suganthi - Diagnostics, 2022 - mdpi.com
In biomedical image analysis, information about the location and appearance of tumors and
lesions is indispensable to aid doctors in treating and identifying the severity of diseases …
lesions is indispensable to aid doctors in treating and identifying the severity of diseases …
LMBiS-Net: A lightweight bidirectional skip connection based multipath CNN for retinal blood vessel segmentation
Blinding eye diseases are often related to changes in retinal structure, which can be
detected by analysing retinal blood vessels in fundus images. However, existing techniques …
detected by analysing retinal blood vessels in fundus images. However, existing techniques …
A survey of deep learning for retinal blood vessel segmentation methods: taxonomy, trends, challenges and future directions
OO Sule - IEEE Access, 2022 - ieeexplore.ieee.org
Recent advancements in deep learning architectures have extended their application to
computer vision tasks, one of which is the segmentation of retinal blood vessels from retinal …
computer vision tasks, one of which is the segmentation of retinal blood vessels from retinal …
A novel framework for retinal vessel segmentation using optimal improved frangi filter and adaptive weighted spatial FCM
Medical attention has long been focused on diagnosing diseases through retinal
vasculature. However, due to the image intensity inhomogeneity and retinal vessel thickness …
vasculature. However, due to the image intensity inhomogeneity and retinal vessel thickness …
SegR-Net: A deep learning framework with multi-scale feature fusion for robust retinal vessel segmentation
Retinal vessel segmentation is an important task in medical image analysis and has a
variety of applications in the diagnosis and treatment of retinal diseases. In this paper, we …
variety of applications in the diagnosis and treatment of retinal diseases. In this paper, we …
ODGNet: a deep learning model for automated optic disc localization and glaucoma classification using fundus images
Glaucoma is one of the prevalent causes of blindness in the modern world. It is a salient
chronic eye disease that leads to irreversible vision loss. The impediments of glaucoma can …
chronic eye disease that leads to irreversible vision loss. The impediments of glaucoma can …