Radiology imaging scans for early diagnosis of kidney tumors: a review of data analytics-based machine learning and deep learning approaches
Plenty of disease types exist in world communities that can be explained by humans'
lifestyles or the economic, social, genetic, and other factors of the country of residence …
lifestyles or the economic, social, genetic, and other factors of the country of residence …
Anatomy-aided deep learning for medical image segmentation: a review
Deep learning (DL) has become widely used for medical image segmentation in recent
years. However, despite these advances, there are still problems for which DL-based …
years. However, despite these advances, there are still problems for which DL-based …
Dodnet: Learning to segment multi-organ and tumors from multiple partially labeled datasets
Due to the intensive cost of labor and expertise in annotating 3D medical images at a voxel
level, most benchmark datasets are equipped with the annotations of only one type of …
level, most benchmark datasets are equipped with the annotations of only one type of …
Region-to-boundary deep learning model with multi-scale feature fusion for medical image segmentation
Accurately locating and segmenting lesions, organs, and tissues from medical images are
necessary prerequisites for disease diagnosis, monitoring, and treatment planning …
necessary prerequisites for disease diagnosis, monitoring, and treatment planning …
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 …
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 …
[HTML][HTML] MSS U-Net: 3D segmentation of kidneys and tumors from CT images with a multi-scale supervised U-Net
Accurate segmentation of kidneys and kidney tumors is an essential step for radiomic
analysis as well as developing advanced surgical planning techniques. In clinical analysis …
analysis as well as developing advanced surgical planning techniques. In clinical analysis …
Brain tumor segmentation of multi-modality MR images via triple intersecting U-Nets
J Zhang, J Zeng, P Qin, L Zhao - Neurocomputing, 2021 - Elsevier
In this paper, we propose a triple intersecting U-Nets (TIU-Nets) for brain glioma
segmentation. First, the proposed TIU-Nets is composed of binary-class segmentation U-Net …
segmentation. First, the proposed TIU-Nets is composed of binary-class segmentation U-Net …
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 …