Gastrointestinal Disorder Detection with a Transformer Based Approach

2022-10-06 · A. K. M. Salman Hosain, Mynul islam, Md Humaion Kabir Mehedi, Irteza Enan Kabir, Zarin Tasnim Khan

Accurate disease categorization using endoscopic images is a significant problem in Gastroenterology. This paper describes a technique for assisting medical diagnosis procedures and identifying gastrointestinal tract disorders based on the categorization of characteristics taken from endoscopic pictures using a vision transformer and transfer learning model. Vision transformer has shown very promising results on difficult image classification tasks. In this paper, we have suggested a vision transformer based approach to detect gastrointestianl diseases from wireless capsule endoscopy (WCE) curated images of colon with an accuracy of 95.63\%. We have compared this transformer based approach with pretrained convolutional neural network (CNN) model DenseNet201 and demonstrated that vision transformer surpassed DenseNet201 in various quantitative performance evaluation metrics.

📄 PDF Abstract BibTeX arXiv:2210.03168

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image-classification Image Classification Medical Diagnosis Transfer Learning

Methods 이 논문이 사용한 방법론

Attention 설명 없음

Linear Layer A Linear Layer is a projection $\mathbf{XW + b}$.

Softmax The Softmax output function transforms a previous layer's output into a vector of probabilities. It is commonly used for multiclass classification. Given an input vector $x$…

Layer Normalization Unlike batch normalization, Layer Normalization directly estimates the normalization statistics from the summed inputs…

Residual Connection 설명 없음

Multi-Head Attention 설명 없음

Dense Connections Dense Connections, or Fully Connected Connections, are a type of layer in a deep neural network that use a linear operation where every input is connected to every output…

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Endoscopic procedures such as esophagogastroduodenoscopy (EGD) and colonoscopy play a critical role in diagnosing and managing gastrointestinal (GI) disorders. However, the documentation burden associated with these proc…

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2025-09-30 · Sumaiya Tabassum, Md. Faysal Ahamed, Hafsa Binte Kibria, Md. Nahiduzzaman 외 arxiv

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Ensemble Learning Data Augmentation

Automated Bleeding Detection and Classification in Wireless Capsule Endoscopy with YOLOv8-X

2024-12-21 · Pavan C Shekar, Vivek Kanhangad, Shishir Maheshwari, T Sunil Kumar

Gastrointestinal (GI) bleeding, a critical indicator of digestive system disorders, re quires efficient and accurate detection methods. This paper presents our solution to the Auto-WCEBleedGen Version V1 Challenge, where…

Position

Classification of Endoscopy and Video Capsule Images using CNN-Transformer Model

2024-08-20 · Aliza Subedi, Smriti Regmi, Nisha Regmi, Bhumi Bhusal 외

Gastrointestinal cancer is a leading cause of cancer-related incidence and death, making it crucial to develop novel computer-aided diagnosis systems for early detection and enhanced treatment. Traditional approaches rel…