Sep 19, 2018 · (1). We propose a new cascaded convolutional neural network framework to address the medical image classification problem with partial ...

In this paper, we propose a cascaded convolutional neural network framework to classify partially annotated pathological images. A segmentation model is trained ...

Article "Partially Annotated Gastric Pathological Image Classification" Detailed information of the J-GLOBAL is an information service managed by the Japan ...

Jun 26, 2021 · In this review, the CAD technique on pathological images of gastric cancer is summarized. Firstly, the paper summarizes the image preprocessing methods.

In this review paper, we will discuss the current histological, molecular, and immunohistochemical classifications of the most common gastrointestinal cancers.

Jun 21, 2018 · This paper presents a novel stepwise fine-tuning-based deep learning scheme for gastric pathology image classification and establishes a new type of target- ...

This review explores the recent advancements, applications, and challenges associated with FMs in endoscopy and pathology imaging.

Dec 20, 2017 · In this paper, a reiterative learning framework was presented to train our network on partial annotated biomedical images, and superior ...

In this paper, we propose a cascaded convolutional neural network framework to classify partially annotated pathological images. A segmentation model is trained ...

Jun 30, 2021 · In this paper, we trained deep learning models using transfer learning, fully-supervised learning, and weakly-supervised learning to predict SRCC in Whole ...