ANet: Nuclei Instance Segmentation and Classification with Attention-Based Network
M Kadaskar, N Patil - SN Computer Science, 2024 - Springer
The segmentation and classification of nuclei in haematoxylin and eosin-stained images is
critical for diagnosing cancer and other disorders. Developing automated methods is …
critical for diagnosing cancer and other disorders. Developing automated methods is …
HDA-Net: H&E and RGB Dual Attention Network for Nuclei Instance Segmentation
YH Im, SH Park, SC Lee - IEEE Access, 2024 - ieeexplore.ieee.org
H&E-stained images (HSIs) are widely adopted for revealing cellular structures and
capturing morphological changes in nuclear instance segmentation. Despite several studies …
capturing morphological changes in nuclear instance segmentation. Despite several studies …
From Pixels to Prognosis: A Survey on AI-Driven Cancer Patient Survival Prediction Using Digital Histology Images
Survival analysis is an integral part of medical statistics that is extensively utilized to
establish prognostic indices for mortality or disease recurrence, assess treatment efficacy …
establish prognostic indices for mortality or disease recurrence, assess treatment efficacy …
Probability-Based Nuclei Detection and Critical-Region Guided Instance Segmentation
Y Zhong, X Li, H Mei, S Xiong - Chinese Conference on Pattern …, 2023 - Springer
Nuclear instance segmentation in histopathological images is a key procedure in
pathological diagnosis. In this regard, a typical class of solutions are deep learning-like …
pathological diagnosis. In this regard, a typical class of solutions are deep learning-like …
[引用][C] Research challenges and emerging futuristic evolution for 3D medical image processing
V Upadhyaya, NK Gupta - 2024 - Elsevier