The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 challenge
There is a large body of literature linking anatomic and geometric characteristics of kidney
tumors to perioperative and oncologic outcomes. Semantic segmentation of these tumors …
tumors to perioperative and oncologic outcomes. Semantic segmentation of these tumors …
Deep learning techniques for tumor segmentation: a review
Recently, deep learning, especially convolutional neural networks, has achieved the
remarkable results in natural image classification and segmentation. At the same time, in the …
remarkable results in natural image classification and segmentation. At the same time, in the …
[HTML][HTML] Volumetric memory network for interactive medical image segmentation
Despite recent progress of automatic medical image segmentation techniques, fully
automatic results usually fail to meet clinically acceptable accuracy, thus typically require …
automatic results usually fail to meet clinically acceptable accuracy, thus typically require …
Kidney tumor semantic segmentation using deep learning: A survey of state-of-the-art
A Abdelrahman, S Viriri - Journal of imaging, 2022 - mdpi.com
Cure rates for kidney cancer vary according to stage and grade; hence, accurate diagnostic
procedures for early detection and diagnosis are crucial. Some difficulties with manual …
procedures for early detection and diagnosis are crucial. Some difficulties with manual …
Automatic segmentation of tumors and affected organs in the abdomen using a 3D hybrid model for computed tomography imaging
Automatic segmentation on computed tomography images of kidney and liver tumors
remains a challenging task due to heterogeneity and variation in shapes. Recently, two …
remains a challenging task due to heterogeneity and variation in shapes. Recently, two …
Efficientnet family u-net models for deep learning semantic segmentation of kidney tumors on ct images
A Abdelrahman, S Viriri - Frontiers in Computer Science, 2023 - frontiersin.org
Introduction Kidney tumors are common cancer in advanced age, and providing early
detection is crucial. Medical imaging and deep learning methods are increasingly attractive …
detection is crucial. Medical imaging and deep learning methods are increasingly attractive …
Random data augmentation based enhancement: a generalized enhancement approach for medical datasets
Over the years, the paradigm of medical image analysis has shifted from manual expertise to
automated systems, often using deep learning (DL) systems. The performance of deep …
automated systems, often using deep learning (DL) systems. The performance of deep …
Crosslink-net: double-branch encoder network via fusing vertical and horizontal convolutions for medical image segmentation
Accurate image segmentation plays a crucial role in medical image analysis, yet it faces
great challenges caused by various shapes, diverse sizes, and blurry boundaries. To …
great challenges caused by various shapes, diverse sizes, and blurry boundaries. To …
Radiomics and artificial intelligence: Renal cell carcinoma
Renal cell carcinoma (RCC) accounts for 90% of primary renal cancers and represents a
significant cause of morbidity and mortality worldwide. Kidney cancer is the 14th most …
significant cause of morbidity and mortality worldwide. Kidney cancer is the 14th most …
Graph-constrained contrastive regularization for semi-weakly volumetric segmentation
Semantic volume segmentation suffers from the requirement of having voxel-wise annotated
ground-truth data, which requires immense effort to obtain. In this work, we investigate how …
ground-truth data, which requires immense effort to obtain. In this work, we investigate how …