Medical image segmentation: A review of modern architectures
N Salpea, P Tzouveli, D Kollias - European Conference on Computer …, 2022 - Springer
Medical image segmentation involves identifying regions of interest in medical images. In
modern times, there is a great need to develop robust computer vision algorithms to perform …
modern times, there is a great need to develop robust computer vision algorithms to perform …
Polyp-pvt: Polyp segmentation with pyramid vision transformers
Most polyp segmentation methods use CNNs as their backbone, leading to two key issues
when exchanging information between the encoder and decoder: 1) taking into account the …
when exchanging information between the encoder and decoder: 1) taking into account the …
On evaluation metrics for medical applications of artificial intelligence
Clinicians and software developers need to understand how proposed machine learning
(ML) models could improve patient care. No single metric captures all the desirable …
(ML) models could improve patient care. No single metric captures all the desirable …
Colorectal polyp region extraction using saliency detection network with neutrosophic enhancement
Colorectal polyp recognition is crucial for early colorectal cancer detection and treatment.
Colonoscopy is always employed for colorectal polyp scanning. However, one out of four …
Colonoscopy is always employed for colorectal polyp scanning. However, one out of four …
A survey on deep learning for polyp segmentation: Techniques, challenges and future trends
Early detection and assessment of polyps play a crucial role in the prevention and treatment
of colorectal cancer (CRC). Polyp segmentation provides an effective solution to assist …
of colorectal cancer (CRC). Polyp segmentation provides an effective solution to assist …
[HTML][HTML] High-precision multiclass classification of lung disease through customized MobileNetV2 from chest X-ray images
In this study, multiple lung diseases are diagnosed with the help of the Neural Network
algorithm. Specifically, Emphysema, Infiltration, Mass, Pleural Thickening, Pneumonia …
algorithm. Specifically, Emphysema, Infiltration, Mass, Pleural Thickening, Pneumonia …
Real-time polyp detection, localization and segmentation in colonoscopy using deep learning
Computer-aided detection, localization, and segmentation methods can help improve
colonoscopy procedures. Even though many methods have been built to tackle automatic …
colonoscopy procedures. Even though many methods have been built to tackle automatic …
TGANet: Text-guided attention for improved polyp segmentation
Colonoscopy is a gold standard procedure but is highly operator-dependent. Automated
polyp segmentation, a precancerous precursor, can minimize missed rates and timely …
polyp segmentation, a precancerous precursor, can minimize missed rates and timely …
HSNet: A hybrid semantic network for polyp segmentation
Automatic polyp segmentation can help physicians to effectively locate polyps (aka region of
interests) in clinical practice, in the way of screening colonoscopy images assisted by neural …
interests) in clinical practice, in the way of screening colonoscopy images assisted by neural …
[HTML][HTML] Focus U-Net: A novel dual attention-gated CNN for polyp segmentation during colonoscopy
Background Colonoscopy remains the gold-standard screening for colorectal cancer.
However, significant miss rates for polyps have been reported, particularly when there are …
However, significant miss rates for polyps have been reported, particularly when there are …