Information mismatch in PHH3-assisted mitosis annotation leads to interpretation shifts in H&E slide analysis
The count of mitotic figures (MFs) observed in hematoxylin and eosin (H&E)-stained slides is
an important prognostic marker, as it is a measure for tumor cell proliferation. However, the …
an important prognostic marker, as it is a measure for tumor cell proliferation. However, the …
Towards a generalizable pathology foundation model via unified knowledge distillation
Foundation models pretrained on large-scale datasets are revolutionizing the field of
computational pathology (CPath). The generalization ability of foundation models is crucial …
computational pathology (CPath). The generalization ability of foundation models is crucial …
A deep learning framework deploying segment anything to detect pan-cancer mitotic figures from haematoxylin and eosin-stained slides
Mitotic activity is an important feature for grading several cancer types. However, counting
mitotic figures (cells in division) is a time-consuming and laborious task prone to inter …
mitotic figures (cells in division) is a time-consuming and laborious task prone to inter …
Breast cancer survival prediction using an automated mitosis detection pipeline
Mitotic count (MC) is the most common measure to assess tumor proliferation in breast
cancer patients and is highly predictive of patient outcomes. It is, however, subject to inter …
cancer patients and is highly predictive of patient outcomes. It is, however, subject to inter …
Nuclear pleomorphism in canine cutaneous mast cell tumors: Comparison of reproducibility and prognostic relevance between estimates, manual morphometry, and …
A Haghofer, E Parlak, A Bartel… - Veterinary …, 2024 - journals.sagepub.com
Variation in nuclear size and shape is an important criterion of malignancy for many tumor
types; however, categorical estimates by pathologists have poor reproducibility …
types; however, categorical estimates by pathologists have poor reproducibility …
Dynamic Pseudo Label Optimization in Point-Supervised Nuclei Segmentation
Deep learning has achieved impressive results in nuclei segmentation, but the massive
requirement for pixel-wise labels remains a significant challenge. To alleviate the annotation …
requirement for pixel-wise labels remains a significant challenge. To alleviate the annotation …
Benchmarking Domain Generalization Algorithms in Computational Pathology
N Zamanitajeddin, M Jahanifar, K Xu, F Siraj… - arXiv preprint arXiv …, 2024 - arxiv.org
Deep learning models have shown immense promise in computational pathology (CPath)
tasks, but their performance often suffers when applied to unseen data due to domain shifts …
tasks, but their performance often suffers when applied to unseen data due to domain shifts …
CPath-Omni: A Unified Multimodal Foundation Model for Patch and Whole Slide Image Analysis in Computational Pathology
The emergence of large multimodal models (LMMs) has brought significant advancements
to pathology. Previous research has primarily focused on separately training patch-level and …
to pathology. Previous research has primarily focused on separately training patch-level and …
Cross-Task Pretraining for Cross-Organ Cross-Scanner Adenocarcinoma Segmentation
A Galdran - arXiv preprint arXiv:2410.07124, 2024 - arxiv.org
This short abstract describes a solution to the COSAS 2024 competition on Cross-Organ and
Cross-Scanner Adenocarcinoma Segmentation from histopathological image patches. The …
Cross-Scanner Adenocarcinoma Segmentation from histopathological image patches. The …
Cross-Organ and Cross-Scanner Adenocarcinoma Segmentation using Rein to Fine-tune Vision Foundation Models
P Cai, X Zhang, L Lan, Z Zhao - arXiv preprint arXiv:2409.11752, 2024 - arxiv.org
In recent years, significant progress has been made in tumor segmentation within the field of
digital pathology. However, variations in organs, tissue preparation methods, and image …
digital pathology. However, variations in organs, tissue preparation methods, and image …