Application of deep learning in histopathology images of breast cancer: a review
With the development of artificial intelligence technology and computer hardware functions,
deep learning algorithms have become a powerful auxiliary tool for medical image analysis …
deep learning algorithms have become a powerful auxiliary tool for medical image analysis …
A ViT-AMC network with adaptive model fusion and multiobjective optimization for interpretable laryngeal tumor grading from histopathological images
The tumor grading of laryngeal cancer pathological images needs to be accurate and
interpretable. The deep learning model based on the attention mechanism-integrated …
interpretable. The deep learning model based on the attention mechanism-integrated …
Scale-aware transformers for diagnosing melanocytic lesions
Diagnosing melanocytic lesions is one of the most challenging areas of pathology with
extensive intra-and inter-observer variability. The gold standard for a diagnosis of invasive …
extensive intra-and inter-observer variability. The gold standard for a diagnosis of invasive …
Identify representative samples by conditional random field of cancer histology images
Pathology analysis is crucial to precise cancer diagnoses and the succeeding treatment
plan as well. To detect abnormality in histopathology images with prevailing patch-based …
plan as well. To detect abnormality in histopathology images with prevailing patch-based …
Adaptive magnification network for precise tumor analysis in histopathological images
The variable magnification levels in histopathology images make it difficult to accurately
categorize tumor regions in breast cancer histology. In this study, a novel architecture for …
categorize tumor regions in breast cancer histology. In this study, a novel architecture for …
Improving the diagnosis of skin biopsies using tissue segmentation
Invasive melanoma, a common type of skin cancer, is considered one of the deadliest.
Pathologists routinely evaluate melanocytic lesions to determine the amount of atypia, and if …
Pathologists routinely evaluate melanocytic lesions to determine the amount of atypia, and if …
Semantics-aware attention guidance for diagnosing whole slide images
Accurate cancer diagnosis remains a critical challenge in digital pathology, largely due to
the gigapixel size and complex spatial relationships present in whole slide images …
the gigapixel size and complex spatial relationships present in whole slide images …
Attribution-Based Confidence Metric for Detection of Adversarial Attacks on Breast Histopathological Images
In this paper, we develop attribution-based confidence (ABC) metric to detect black-box
adversarial attacks in breast histopathology images. Due to the lack of data for this problem …
adversarial attacks in breast histopathology images. Due to the lack of data for this problem …
Advancing Tumor Cell Classification and Segmentation in Ki-67 Images: A Systematic Review of Deep Learning Approaches
M Zaki, O Elallam, O Jami, D EL Ghoubali… - … on Advanced Intelligent …, 2023 - Springer
Breast cancer is one of the most diagnosed cancers, transforming it into a matter of great
concern for public health. Early detection increases the probability of effective therapy and …
concern for public health. Early detection increases the probability of effective therapy and …
Efficient Metric Learning with Graph Transformer for Accurate Colorectal Cancer Staging
Z Pei, D Zhang, W Shao - 2022 IEEE-EMBS International …, 2022 - ieeexplore.ieee.org
Colorectal cancer (CRC) is the third leading cause of cancer death in men and the third
leading cause of cancer death in women in United States. So far, the histopathological …
leading cause of cancer death in women in United States. So far, the histopathological …