Recent advancements in artificial intelligence for breast cancer: Image augmentation, segmentation, diagnosis, and prognosis approaches
Breast cancer is a significant global health burden, with increasing morbidity and mortality
worldwide. Early screening and accurate diagnosis are crucial for improving prognosis …
worldwide. Early screening and accurate diagnosis are crucial for improving prognosis …
HCTNet: A hybrid CNN-transformer network for breast ultrasound image segmentation
Q He, Q Yang, M Xie - Computers in Biology and Medicine, 2023 - Elsevier
Automatic breast ultrasound image segmentation helps radiologists to improve the accuracy
of breast cancer diagnosis. In recent years, the convolutional neural networks (CNNs) have …
of breast cancer diagnosis. In recent years, the convolutional neural networks (CNNs) have …
[HTML][HTML] Deep learning for medical image segmentation: State-of-the-art advancements and challenges
Image segmentation, a crucial process of dividing images into distinct parts or objects, has
witnessed remarkable advancements with the emergence of deep learning (DL) techniques …
witnessed remarkable advancements with the emergence of deep learning (DL) techniques …
Arf-net: An adaptive receptive field network for breast mass segmentation in whole mammograms and ultrasound images
UNet adopting an encoder-decoder structure has been used widely in medical image
segmentation tasks for its outstanding performance. However, in our work, we find that UNet …
segmentation tasks for its outstanding performance. However, in our work, we find that UNet …
Residual attention based uncertainty-guided mean teacher model for semi-supervised breast masses segmentation in 2D ultrasonography
Breast tumor is the second deadliest disease among women around the world. Earlier tumor
diagnosis is extremely important for improving the survival rate. Recent deep-learning …
diagnosis is extremely important for improving the survival rate. Recent deep-learning …
Boundary-guided and region-aware network with global scale-adaptive for accurate segmentation of breast tumors in ultrasound images
Breast ultrasound (BUS) image segmentation is a critical procedure in the diagnosis and
quantitative analysis of breast cancer. Most existing methods for BUS image segmentation …
quantitative analysis of breast cancer. Most existing methods for BUS image segmentation …
A novel convolutional neural network for kidney ultrasound images segmentation
Abstract Background and Objective: Ultrasound imaging has been widely used in the
screening of kidney diseases. The localization and segmentation of the kidneys in …
screening of kidney diseases. The localization and segmentation of the kidneys in …
A discriminative level set method with deep supervision for breast tumor segmentation
Background: Breast tumor segmentation in B-mode ultrasound imaging is important for
analyzing, identifying, and diagnosing tumors. The level set is an approach most widely …
analyzing, identifying, and diagnosing tumors. The level set is an approach most widely …
Cross-image dependency modeling for breast ultrasound segmentation
H Wu, X Huang, X Guo, Z Wen… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
We present a novel deep network (namely BUSSeg) equipped with both within-and cross-
image long-range dependency modeling for automated lesions segmentation from breast …
image long-range dependency modeling for automated lesions segmentation from breast …
MBANet: Multi-branch aware network for kidney ultrasound images segmentation
Due to the influence of kidney morphology, heterogeneous structure and image quality,
segmenting kidney in ultrasound images is challenging. To alleviate this challenge, we …
segmenting kidney in ultrasound images is challenging. To alleviate this challenge, we …