DeepAI AI Chat
Log In Sign Up

Deep Object Detection based Mitosis Analysis in Breast Cancer Histopathological Images

by   Anabia Sohail, et al.

Empirical evaluation of breast tissue biopsies for mitotic nuclei detection is considered an important prognostic biomarker in tumor grading and cancer progression. However, automated mitotic nuclei detection poses several challenges because of the unavailability of pixel-level annotations, different morphological configurations of mitotic nuclei, their sparse representation, and close resemblance with non-mitotic nuclei. These challenges undermine the precision of the automated detection model and thus make detection difficult in a single phase. This work proposes an end-to-end detection system for mitotic nuclei identification in breast cancer histopathological images. Deep object detection-based Mask R-CNN is adapted for mitotic nuclei detection that initially selects the candidate mitotic region with maximum recall. However, in the second phase, these candidate regions are refined by multi-object loss function to improve the precision. The performance of the proposed detection model shows improved discrimination ability (F-score of 0.86) for mitotic nuclei with significant precision (0.86) as compared to the two-stage detection models (F-score of 0.701) on TUPAC16 dataset. Promising results suggest that the deep object detection-based model has the potential to learn the characteristic features of mitotic nuclei from weakly annotated data and suggests that it can be adapted for the identification of other nuclear bodies in histopathological images.


page 6

page 8

page 9

page 10

page 17


Deep learning-based Subtyping of Atypical and Normal Mitoses using a Hierarchical Anchor-Free Object Detector

Mitotic activity is key for the assessment of malignancy in many tumors....

Cancerous Nuclei Detection and Scoring in Breast Cancer Histopathological Images

Early detection and prognosis of breast cancer are feasible by utilizing...

Increasing the usefulness of already existing annotations through WSI registration

Computational pathology methods have the potential to improve access to ...

Automated Scoring of Nuclear Pleomorphism Spectrum with Pathologist-level Performance in Breast Cancer

Nuclear pleomorphism is the degree of change in nuclear morphology, one ...

Multi-stream Faster RCNN for Mitosis Counting in Breast Cancer Images

Mitotic count is a commonly used method to assess the level of progressi...