Paper Review

1.[2021 Computers in Biology and Medicine] The impact of pre- and post-image processing techniques on deep learning frameworks: A comprehensive review for digital pathology image analysis

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2.[2022 arXiv] What Makes Transfer Learning Work For Medical Images: Feature Reuse & Other Factors

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3.[2022 arXiv] Full-Spectrum Out-of-Distribution Detection

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4.[2021 Computerized Medical Imaging and Graphics] Deep Multi-Magnification Networks for Multi-Class Breast Cancer Image Segmentation

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5.[2022 CVPR] Rethinking Semantic Segmentation: A Prototype View

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6.[2019 PMLR, ICML] SelectiveNet: A Deep Neural Network with an Integrated Reject Option

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7.[2017 MICCAI] Suggestive Annotation: A Deep Active Learning Framework for Biomedical Image Segmentation

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8.[2022 CVPR] Towards Fewer Annotations : Active Learning via Region Impurity and Prediction Uncertainty for Domain Adaptive Semantic Segmentation

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9.[2019 MIA] Hover-Net: Simultaneous segmentation and classification of nuclei in multi-tissue histology images

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10.[2022 npj Digital Medicine] Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations

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11.[2022 Frontiers in Immunology] Artificial Intelligence-Assisted Score Analysis for Predicting the Expression of the Immunotherapy Biomarker PD-L1 in Lung Cancer

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12.[MIA 2020] Triple U-Net: Hematoxylin-aware Nuclei Segmentation with Progressive Dense Feature Aggregation

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13.[2022 arXiv] MobileViTv3: Mobile-Friendly Vision Transformer with Simple and Effective Fusion of Local, Global and Input Features

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14.[CVPR 2022] TopFormer: Token Pyramid Transformer for Mobile Semantic Segmentation

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15.[NIPS 2021] SegFormer: Simple and efficient design for semantic segmentation with transformers

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16.[2021 NIPS] Focal Attention for Long-Range Interactions in Vision Transformers

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17.[2022 MICCAI] Unsupervised Nuclei Segmentation using Spatial Organization Priors

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18.[2022 CVPR] A ConvNet for the 2020s (ConvNeXt)

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19.[2023 CVPR] Revisiting Weak-to-Strong Consistency in Semi-Supervised Semantic Segmentation

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21.[2021 ICIP] Attention toward neighbors: A context aware framework for high resolution image segmentation

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22.[CVPR 2023] AutoFocusFormer: Image Segmentation off the Grid

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23.[2023 MICCAI] Segment Membranes and Nuclei from Histopathological Images via Nuclei Point-Level Supervision

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24.[NIPS 2022] SegNeXt: Rethinking Convolutional Attention Design for Semantic Segmentation

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25.[NIPS 2020] Self-adaptive training: Beyond empirical risk minimization

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