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A brief survey on semantic segmentation with deep learning
Semantic segmentation is a challenging task in computer vision. In recent years, the
performance of semantic segmentation has been greatly improved by using deep learning …
performance of semantic segmentation has been greatly improved by using deep learning …
Deep learning techniques for liver and liver tumor segmentation: A review
Liver and liver tumor segmentation from 3D volumetric images has been an active research
area in the medical image processing domain for the last few decades. The existence of …
area in the medical image processing domain for the last few decades. The existence of …
Generative adversarial network in medical imaging: A review
Generative adversarial networks have gained a lot of attention in the computer vision
community due to their capability of data generation without explicitly modelling the …
community due to their capability of data generation without explicitly modelling the …
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 …
GANs for medical image analysis
Generative adversarial networks (GANs) and their extensions have carved open many
exciting ways to tackle well known and challenging medical image analysis problems such …
exciting ways to tackle well known and challenging medical image analysis problems such …
A survey on generative adversarial networks for imbalance problems in computer vision tasks
Any computer vision application development starts off by acquiring images and data, then
preprocessing and pattern recognition steps to perform a task. When the acquired images …
preprocessing and pattern recognition steps to perform a task. When the acquired images …
Tackling class imbalance in computer vision: a contemporary review
Class imbalance is a key issue affecting the performance of computer vision applications
such as medical image analysis, objection detection and recognition, image segmentation …
such as medical image analysis, objection detection and recognition, image segmentation …
Deep learning in multi-organ segmentation
This paper presents a review of deep learning (DL) in multi-organ segmentation. We
summarized the latest DL-based methods for medical image segmentation and applications …
summarized the latest DL-based methods for medical image segmentation and applications …
Evaluation of preprocessing techniques for U-Net based automated liver segmentation
To extract liver from medical images is a challenging task due to similar intensity values of
liver with adjacent organs, various contrast levels, various noise associated with medical …
liver with adjacent organs, various contrast levels, various noise associated with medical …
Deep learning architecture design for multi-organ segmentation
This chapter presents a review of the recent advancements of the deep learning (DL)-based
medical image multi-organ segmentation methods. The latest network architecture designs …
medical image multi-organ segmentation methods. The latest network architecture designs …