A review of medical image data augmentation techniques for deep learning applications
Research in artificial intelligence for radiology and radiotherapy has recently become
increasingly reliant on the use of deep learning‐based algorithms. While the performance of …
increasingly reliant on the use of deep learning‐based algorithms. While the performance of …
A review of deep learning based methods for medical image multi-organ segmentation
Deep learning has revolutionized image processing and achieved the-state-of-art
performance in many medical image segmentation tasks. Many deep learning-based …
performance in many medical image segmentation tasks. Many deep learning-based …
A comprehensive study on colorectal polyp segmentation with ResUNet++, conditional random field and test-time augmentation
Colonoscopy is considered the gold standard for detection of colorectal cancer and its
precursors. Existing examination methods are, however, hampered by high overall miss …
precursors. Existing examination methods are, however, hampered by high overall miss …
Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge
Polyps are well-known cancer precursors identified by colonoscopy. However, variability in
their size, appearance, and location makes the detection of polyps challenging. Moreover …
their size, appearance, and location makes the detection of polyps challenging. Moreover …
Image segmentation techniques: statistical, comprehensive, semi-automated analysis and an application perspective analysis of mathematical expressions
Segmentation has been a rooted area of research having diverse dimensions. The roots of
image segmentation and its associated techniques have supported computer vision, pattern …
image segmentation and its associated techniques have supported computer vision, pattern …
Learn to threshold: Thresholdnet with confidence-guided manifold mixup for polyp segmentation
The automatic segmentation of polyp in endoscopy images is crucial for early diagnosis and
cure of colorectal cancer. Existing deep learning-based methods for polyp segmentation …
cure of colorectal cancer. Existing deep learning-based methods for polyp segmentation …
Where do we stand in AI for endoscopic image analysis? Deciphering gaps and future directions
S Ali - npj Digital Medicine, 2022 - nature.com
Recent developments in deep learning have enabled data-driven algorithms that can reach
human-level performance and beyond. The development and deployment of medical image …
human-level performance and beyond. The development and deployment of medical image …
Improving load forecasting process for a power distribution network using hybrid AI and deep learning algorithms
S Motepe, AN Hasan, R Stopforth - IEEE Access, 2019 - ieeexplore.ieee.org
Load forecasting is useful for various applications, including maintenance planning. The
study of load forecasting using recent state-of-the-art hybrid artificial intelligence (AI) and …
study of load forecasting using recent state-of-the-art hybrid artificial intelligence (AI) and …
A State‐of‐the‐Art Review for Gastric Histopathology Image Analysis Approaches and Future Development
S Ai, C Li, X Li, T Jiang, M Grzegorzek… - BioMed Research …, 2021 - Wiley Online Library
Gastric cancer is a common and deadly cancer in the world. The gold standard for the
detection of gastric cancer is the histological examination by pathologists, where Gastric …
detection of gastric cancer is the histological examination by pathologists, where Gastric …
A survey of medical image analysis using deep learning approaches
With the expanding development of Deep Learning techniques Medical Image Analysis
have become an active field of research. Medical Image Analysis typically refers to the …
have become an active field of research. Medical Image Analysis typically refers to the …