Learning New Tricks from Old Dogs – Inter-Species, Inter-Tissue Domain Adaptation for Mitotic Figure Assessment

11/25/2019
by   Marc Aubreville, et al.
23

For histopathological tumor assessment, the count of mitotic figures per area is an important part of prognostication. Algorithmic approaches - such as for mitotic figure identification - have significantly improved in recent times, potentially allowing for computer-augmented or fully automatic screening systems in the future. This trend is further supported by whole slide scanning microscopes becoming available in many pathology labs and could soon become a standard imaging tool. For an application in broader fields of such algorithms, the availability of mitotic figure data sets of sufficient size for the respective tissue type and species is an important precondition, that is, however, rarely met. While algorithmic performance climbed steadily for e.g. human mammary carcinoma, thanks to several challenges held in the field, for most tumor types, data sets are not available. In this work, we assess domain transfer of mitotic figure recognition using domain adversarial training on four data sets, two from dogs and two from humans. We were able to show that domain adversarial training considerably improves accuracy when applying mitotic figure classification learned from the canine on the human data sets (up to +12.8 method to transfer knowledge from existing data sets to new tissue types and species.

READ FULL TEXT
research
06/04/2018

Adversarial Domain Adaptation for Classification of Prostate Histopathology Whole-Slide Images

Automatic and accurate Gleason grading of histopathology tissue slides i...
research
03/29/2020

Elastic Coupled Co-clustering for Single-Cell Genomic Data

The recent advances in single-cell technologies have enabled us to profi...
research
11/29/2021

Classification of animal sounds in a hyperdiverse rainforest using Convolutional Neural Networks

To protect tropical forest biodiversity, we need to be able to detect it...
research
05/28/2019

Adversarial Domain Adaptation Being Aware of Class Relationships

Adversarial training is a useful approach to promote the learning of tra...
research
03/18/2018

The Automatic Identification of Butterfly Species

The available butterfly data sets comprise a few limited species, and th...
research
09/17/2021

Primary Tumor and Inter-Organ Augmentations for Supervised Lymph Node Colon Adenocarcinoma Metastasis Detection

The scarcity of labeled data is a major bottleneck for developing accura...
research
02/08/2021

Improving filling level classification with adversarial training

We investigate the problem of classifying - from a single image - the le...

Please sign up or login with your details

Forgot password? Click here to reset