# A Survey on Contemporary Computer-Aided Tumor, Polyp, and Ulcer Detection Methods in Wireless Capsule Endoscopy Imaging

arXiv: https://arxiv.org/abs/1910.00265 · HTML: https://mlsanity.com/paper/1910.00265/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Oct 2019.

## Built on by (most cited first, 7 of 7)

- [Polyp-PVT: Polyp Segmentation with Pyramid Vision Transformers](https://mlsanity.com/paper/2108.06932/) (2021)
- [Lesion2Vec: Deep Metric Learning for Few-Shot Multiple Lesions Recognition in Wireless Capsule Endoscopy Video](https://mlsanity.com/paper/2101.04240/) (2021)
- [Graph Convolution Neural Network For Weakly Supervised Abnormality Localization In Long Capsule Endoscopy Videos](https://mlsanity.com/paper/2110.09110/) (2021)
- [Self-Supervised and Semi-Supervised Polyp Segmentation using Synthetic Data](https://mlsanity.com/paper/2307.12033/) (2023)
- [Unsupervised Shot Boundary Detection for Temporal Segmentation of Long Capsule Endoscopy Videos](https://mlsanity.com/paper/2110.09067/) (2021)
- [Artificial Intelligence in Gastrointestinal Bleeding Analysis for Video Capsule Endoscopy: Insights, Innovations, and Prospects (2008-2023)](https://mlsanity.com/paper/2409.00639/) (2024)
- [PVTAdpNet: Polyp Segmentation using Pyramid vision transformer with a novel Adapter block](https://mlsanity.com/paper/2509.23751/) (2025)

## Abstract (arXiv)

Wireless capsule endoscopy (WCE) is a process in which a patient swallows a camera-embedded pill-shaped device that passes through the gastrointestinal (GI) tract, captures and transmits images to an external receiver. WCE devices are considered as a replacement of conventional endoscopy methods which are usually painful and distressful for the patients. WCE devices produce over 60,000 images typically during their course of operation inside the GI tract. These images need to be examined by expert physicians who attempt to identify frames that contain inflammation / disease. It can be hectic for a physician to go through such a large number of frames, hence computer-aided detection methods are considered an efficient alternative. Various anomalies can take place in the GI tract of a human being but the most important and common ones and the aim of this survey are ulcers, polyps, and tumors. In this paper, we have presented a survey of contemporary computer-aided detection methods that take WCE images as input and classify those images in a diseased/abnormal or disease-free/ normal image. We have considered methods that detect tumors, polyps and ulcers, as these three diseases lie in the same category. Furthermore bleeding inside the GI tract may be the symptoms of these diseases; so an attempt is also made to enlighten the research work done for bleeding detection inside WCE. Several studies have been included with in-depth detail of their methodologies, findings, and conclusions. Also, we have attempted to classify these methods based on their technical aspects. This paper also includes a potential proposal for joint classification of aforementioned three diseases.