U-net and its variants for medical image segmentation: A review of theory and applications
U-net is an image segmentation technique developed primarily for image segmentation
tasks. These traits provide U-net with a high utility within the medical imaging community …
tasks. These traits provide U-net with a high utility within the medical imaging community …
[HTML][HTML] The impact of pre-and post-image processing techniques on deep learning frameworks: A comprehensive review for digital pathology image analysis
Recently, deep learning frameworks have rapidly become the main methodology for
analyzing medical images. Due to their powerful learning ability and advantages in dealing …
analyzing medical images. Due to their powerful learning ability and advantages in dealing …
DenseRes-Unet: Segmentation of overlapped/clustered nuclei from multi organ histopathology images
Cancer is the second deadliest disease globally that can affect any human body organ.
Early detection of cancer can increase the chances of survival in humans. Morphometric …
Early detection of cancer can increase the chances of survival in humans. Morphometric …
A survey on artificial intelligence in histopathology image analysis
The increasing adoption of the whole slide image (WSI) technology in histopathology has
dramatically transformed pathologists' workflow and allowed the use of computer systems in …
dramatically transformed pathologists' workflow and allowed the use of computer systems in …
Breast histopathological image analysis using image processing techniques for diagnostic purposes: A methodological review
Breast cancer in women is the second most common cancer worldwide. Early detection of
breast cancer can reduce the risk of human life. Non-invasive techniques such as …
breast cancer can reduce the risk of human life. Non-invasive techniques such as …
Deep learning in breast cancer imaging: A decade of progress and future directions
Breast cancer has reached the highest incidence rate worldwide among all malignancies
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …
[HTML][HTML] U-Net 网络医学图像分割应用综述
周涛， 董雅丽， 霍兵强， 刘珊， 马宗军 - 2021 - cjig.cn
摘要病灶精确分割对患者病情评估和治疗方案制定有重要意义, 由于医学图像中病灶与周围组织
的对比度低, 同一疾病病灶边缘和形状存在很大差异, 从而增加了分割难度. U-Net …
的对比度低, 同一疾病病灶边缘和形状存在很大差异, 从而增加了分割难度. U-Net …
DAN-NucNet: A dual attention based framework for nuclei segmentation in cancer histology images under wild clinical conditions
Nuclei segmentation plays an essential role in histology analysis. The nuclei segmentation
in histology images is challenging in variable conditions (clinical wild), such as poor staining …
in histology images is challenging in variable conditions (clinical wild), such as poor staining …
Efficient deep learning architecture with dimension-wise pyramid pooling for nuclei segmentation of histopathology images
AA Aatresh, RP Yatgiri, AK Chanchal, A Kumar… - … Medical Imaging and …, 2021 - Elsevier
Image segmentation remains to be one of the most vital tasks in the area of computer vision
and more so in the case of medical image processing. Image segmentation quality is the …
and more so in the case of medical image processing. Image segmentation quality is the …
Continuous refinement-based digital pathology image assistance scheme in medical decision-making systems
J Wu, T Luo, J Zeng, F Gou - IEEE Journal of Biomedical and …, 2024 - ieeexplore.ieee.org
Digital pathology images' extensive cellular information provide a trustworthy foundation for
tumor diagnosis. With the aid of computer-aided diagnostics, pathologists can locate crucial …
tumor diagnosis. With the aid of computer-aided diagnostics, pathologists can locate crucial …