Dec 20, 2017 · In this paper, a reiterative learning framework was presented to train our network on partial annotated biomedical images, and superior ...
... training dataset (b) labels given by authorities (c) ground truth. In this paper, we present a reiterative learning framework to dealing with partial and ...
Qualitative segmentation results on the data set. (a). Partial Labeled Gastric Tumor Segmentation via patch-based Reiterative Learning. Article. Full-text ...
May 30, 2022 · Nan et al. (2017) proposed a reiterative learning framework for partial labeled gastric tumor segmentation. Li et al. (2018) designed two ...
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Partial Labeled Gastric Tumor Segmentation via patch-based Reiterative Learning ... Gastric cancer is the second leading cause of cancer-related deaths worldwide, ...
A State‐of‐the‐Art Review for Gastric Histopathology Image Analysis ...
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Jun 28, 2021 · In [51], the authors propose a gastric cancer histopathological image classification method based on recalibrated multi-instance deep learning.
We propose a novel Deep Active Learning (DeepAL) model-3D Wasserstein Discriminative UNet (WD-UNet) for reducing the annotation effort of medical 3D Computed ...
... image segmentation strategy for images of weakly labeled gastric tumors.26 ... The investigators used partial transfer learning to train their AI-based ...
Article "Partial Labeled Gastric Tumor Segmentation via patch-based Reiterative Learning" Detailed information of the J-GLOBAL is an information service ...
Mar 2, 2017 · ... using the ImageFolder dataset with lots of image patches ... segmentation, I am trying to reproduce a paper based on patch based approach.