A comprehensive multi-domain dataset for mitotic figure detection
The prognostic value of mitotic figures in tumor tissue is well-established for many tumor
types and automating this task is of high research interest. However, especially deep …
types and automating this task is of high research interest. However, especially deep …
[HTML][HTML] Mitosis detection, fast and slow: robust and efficient detection of mitotic figures
M Jahanifar, A Shephard, N Zamanitajeddin… - Medical Image …, 2024 - Elsevier
Counting of mitotic figures is a fundamental step in grading and prognostication of several
cancers. However, manual mitosis counting is tedious and time-consuming. In addition …
cancers. However, manual mitosis counting is tedious and time-consuming. In addition …
Computer-assisted mitotic count using a deep learning–based algorithm improves interobserver reproducibility and accuracy
The mitotic count (MC) is an important histological parameter for prognostication of
malignant neoplasms. However, it has inter-and intraobserver discrepancies due to …
malignant neoplasms. However, it has inter-and intraobserver discrepancies due to …
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 …
Pan-tumor canine cutaneous cancer histology (catch) dataset
Due to morphological similarities, the differentiation of histologic sections of cutaneous
tumors into individual subtypes can be challenging. Recently, deep learning-based …
tumors into individual subtypes can be challenging. Recently, deep learning-based …
Domain generalization in computational pathology: survey and guidelines
Deep learning models have exhibited exceptional effectiveness in Computational Pathology
(CPath) by tackling intricate tasks across an array of histology image analysis applications …
(CPath) by tackling intricate tasks across an array of histology image analysis applications …
Domain-specific cycle-GAN augmentation improves domain generalizability for mitosis detection
As the third-place winning method for the MIDOG mitosis detection challenge, we created a
cascade algorithm consisting of a Mask-RCNN detector, followed by a classification …
cascade algorithm consisting of a Mask-RCNN detector, followed by a classification …
[HTML][HTML] Pan-tumor T-lymphocyte detection using deep neural networks: Recommendations for transfer learning in immunohistochemistry
F Wilm, C Ihling, G Méhes, L Terracciano… - Journal of Pathology …, 2023 - Elsevier
The success of immuno-oncology treatments promises long-term cancer remission for an
increasing number of patients. The response to checkpoint inhibitor drugs has shown a …
increasing number of patients. The response to checkpoint inhibitor drugs has shown a …
On the Value of PHH3 for Mitotic Figure Detection on H&E-stained Images
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 …
A New Approach to Data Annotation Automation for Online Handwritten Mathematical Expression Recognition based on Recurrent Neural Networks
The modern recognition methods based on deep learning have established high
requirements for the size of training data. However, such data is not always publicly …
requirements for the size of training data. However, such data is not always publicly …