MIDOG 2025: Mitotic Figure Detection with Attention-Guided False Positive Correction

Fuente: arXiv
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Main Authors: Broad, Andrew, Keighley, Jason, Godson, Lucy, Wright, Alex
Format: Preprint
Published: 2025
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author Broad, Andrew
Keighley, Jason
Godson, Lucy
Wright, Alex
author_facet Broad, Andrew
Keighley, Jason
Godson, Lucy
Wright, Alex
contents We present a novel approach which extends the existing Fully Convolutional One-Stage Object Detector (FCOS) for mitotic figure detection. Our composite model adds a Feedback Attention Ladder CNN (FAL-CNN) model for classification of normal versus abnormal mitotic figures, feeding into a fusion network that is trained to generate adjustments to bounding boxes predicted by FCOS. Our network aims to reduce the false positive rate of the FCOS object detector, to improve the accuracy of object detection and enhance the generalisability of the network. Our model achieved an F1 score of 0.655 for mitosis detection on the preliminary evaluation dataset.
format Preprint
id arxiv_https___arxiv_org_abs_2509_02598
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle MIDOG 2025: Mitotic Figure Detection with Attention-Guided False Positive Correction
Broad, Andrew
Keighley, Jason
Godson, Lucy
Wright, Alex
Image and Video Processing
Artificial Intelligence
We present a novel approach which extends the existing Fully Convolutional One-Stage Object Detector (FCOS) for mitotic figure detection. Our composite model adds a Feedback Attention Ladder CNN (FAL-CNN) model for classification of normal versus abnormal mitotic figures, feeding into a fusion network that is trained to generate adjustments to bounding boxes predicted by FCOS. Our network aims to reduce the false positive rate of the FCOS object detector, to improve the accuracy of object detection and enhance the generalisability of the network. Our model achieved an F1 score of 0.655 for mitosis detection on the preliminary evaluation dataset.
title MIDOG 2025: Mitotic Figure Detection with Attention-Guided False Positive Correction
topic Image and Video Processing
Artificial Intelligence
url https://arxiv.org/abs/2509.02598