IVCVLGOct 19, 2024

Stool Recognition for Colorectal Cancer Detection through Deep Learning

arXiv:2410.17288v1ICMI
Originality Synthesis-oriented
AI Analysis

This provides a simple, fast, and cost-free tool for early colorectal cancer screening, though it is incremental as it applies existing deep learning methods to a new medical imaging task.

The researchers tackled colorectal cancer detection by developing a stool recognition neural network that identifies blood in stool images as an alternative to traditional FOBT tests, achieving 94% accuracy through GAN-augmented training data and deploying it in a mobile app for instant results.

Colorectal cancer is the most common cancer in Singapore and the third most common cancer worldwide. Blood in a person's stool is a symptom of this disease, and it is usually detected by the faecal occult blood test (FOBT). However, the FOBT presents several limitations - the collection process for the stool samples is tedious and unpleasant, the waiting period for results is about 2 weeks and costs are involved. In this research, we propose a simple-to-use, fast and cost-free alternative - a stool recognition neural network that determines if there is blood in one's stool (which indicates a possible risk of colorectal cancer) from an image of it. As this is a new classification task, there was limited data available, hindering classifier performance. Hence, various Generative Adversarial Networks (GANs) (DiffAugment StyleGAN2, DCGAN, Conditional GAN) were trained to generate images of high fidelity to supplement the dataset. Subsequently, images generated by the GAN with the most realistic images (DiffAugment StyleGAN2) were concatenated to the classifier's training batch on-the-fly, improving accuracy to 94%. This model was then deployed to a mobile app - Poolice, where users can take a photo of their stool and obtain instantaneous results if there is blood in their stool, prompting those who do to seek medical advice. As "early detection saves lives", we hope our app built on our stool recognition neural network can help people detect colorectal cancer earlier, so they can seek treatment and have higher chances of survival.

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