ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging | Paper Citation Record

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This paper cites A survey on self-supervised methods for visual representation learning.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging A survey on self-supervised methods for visual representation learning

Reference 1

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Observation 0143d054-d14d-4bb9-8968-3da9ef8245f1 · outbound

This paper cites Self-supervised learning for medical image analysis: a comprehensive review.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Self-supervised learning for medical image analysis: a comprehensive review

Reference 2

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Observation 27337f1c-4807-4a01-be48-f319876758c3 · outbound

This paper cites Breast cancer classification based on breast tissue structures using the Jigsaw puzzle task in self-supervised learning.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Breast cancer classification based on breast tissue structures using the Jigsaw puzzle task in self-supervised learning

Reference 3

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This paper cites Distributed contrastive learning for medical image segmentation.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Distributed contrastive learning for medical image segmentation

Reference 4

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Observation 31d21a7d-393d-4ebb-a226-9189c7a46a76 · outbound

This paper cites Mim: Mask in mask self-supervised pre-training for 3d medical image analysis.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Mim: Mask in mask self-supervised pre-training for 3d medical image analysis

Reference 5

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Observation 0628cae4-e343-4352-9d39-6b1b5e6eda01 · outbound

This paper cites Robson, Brett Marinelli, Mingqian Huang, Amish Doshi, Adam Jacobi, Chendi Cao, Katherine E.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Robson, Brett Marinelli, Mingqian Huang, Amish Doshi, Adam Jacobi, Chendi Cao, Katherine E

Reference 6

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Observation 68002d71-5ff9-47a3-9b4e-a0a8439117f6 · outbound

This paper cites Vis-mae: An efficient self-supervised learning approach on medical image segmentation and classification.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Vis-mae: An efficient self-supervised learning approach on medical image segmentation and classification

Reference 7

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Observation d5193d1f-85c6-4c53-85a9-8ec52f000ed2 · outbound

This paper cites Rotation- oriented collaborative self-supervised learning for retinal disease diagnosis.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Rotation- oriented collaborative self-supervised learning for retinal disease diagnosis

Reference 8

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Observation d09c7e6a-b2ab-49de-af2a-1dc733c6c21c · outbound

This paper cites A simple framework for contrastive learning of visual representations.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging A simple framework for contrastive learning of visual representations

Reference 9

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This paper cites Momentum contrast for unsupervised visual representation learning.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Momentum contrast for unsupervised visual representation learning

Reference 10

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Observation 167301a2-9e94-46f8-a7e2-e2802bf33dd0 · outbound

This paper cites UKSSL: Underlying knowledge based semi- supervised learning for medical image classification.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging UKSSL: Underlying knowledge based semi- supervised learning for medical image classification

Reference 11

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This paper cites Moco pretraining improves representation and transferability of chest x-ray models.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Moco pretraining improves representation and transferability of chest x-ray models

Reference 12

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Observation e494bbe0-dd63-4235-bcf6-b85d7692c8eb · outbound

This paper cites Gloria: A multimodal global-local rep- resentation learning framework for label-efficient medical image recognition.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Gloria: A multimodal global-local rep- resentation learning framework for label-efficient medical image recognition

Reference 13

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This paper cites Making the most of text semantics to improve biomedical vision–language processing.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Making the most of text semantics to improve biomedical vision–language processing

Reference 14

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Observation b3d83d30-307d-4be5-a2a8-01cdf57c35a7 · outbound

This paper cites Self pre-training with masked autoencoders for medical image classification and segmentation.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Self pre-training with masked autoencoders for medical image classification and segmentation

Reference 15

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Observation 1b053df4-9a6a-49a6-9f95-08f849a91db5 · outbound

This paper cites Advancing V olumetric Medical Image Segmentation via Global-Local Masked Autoencoders.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Advancing V olumetric Medical Image Segmentation via Global-Local Masked Autoencoders

Reference 16

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Observation b16e863f-ca90-4557-aa57-814e8fcfae45 · outbound

This paper cites Swin MAE: masked autoencoders for small datasets.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Swin MAE: masked autoencoders for small datasets

Reference 17

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Observation 9bf8c2bb-0546-4b57-9211-5db32105156e · outbound

This paper cites Unest: local spatial representation learning with hierarchical transformer for efficient medical segmentation.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Unest: local spatial representation learning with hierarchical transformer for efficient medical segmentation

Reference 18

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This paper cites Video-CT MAE: Self-supervised Video-CT Domain Adaptation for Vertebral Fracture Diagnosis.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Video-CT MAE: Self-supervised Video-CT Domain Adaptation for Vertebral Fracture Diagnosis

Reference 19

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This paper cites Self-supervised pre-training of swin transformers for 3d medical image analysis.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Self-supervised pre-training of swin transformers for 3d medical image analysis

Reference 20

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This paper cites Mining multi-label data.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Mining multi-label data

Reference 21

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Observation dabff964-08d2-43ef-948d-7791eb88c86f · outbound

This paper cites Learning multi-label scene classifica- tion.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Learning multi-label scene classifica- tion

Reference 22

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This paper cites ML-KNN: A lazy learning approach to multi-label learning.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging ML-KNN: A lazy learning approach to multi-label learning

Reference 23

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This paper cites A kernel method for multi-labelled classification.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging A kernel method for multi-labelled classification

Reference 24

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This paper cites Cnn-rnn: A unified framework for multi-label image classification.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Cnn-rnn: A unified framework for multi-label image classification

Reference 25

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Observation 0624a22e-0e4d-43ad-9d05-d091c91c0716 · outbound

This paper cites Learning spatial regularization with image-level supervisions for multi-label image classification.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Learning spatial regularization with image-level supervisions for multi-label image classification

Reference 26

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Observation 0a360a4d-34c8-4181-b926-6153d84a1fb4 · outbound

This paper cites Multi-label image recognition with graph con- volutional networks.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Multi-label image recognition with graph con- volutional networks

Reference 27

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Observation 9d0fc067-bac4-4fa3-9d75-995c0469096f · outbound

This paper cites Attentionxml: Label tree-based attention-aware deep model for high-performance extreme multi-label text classification.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Attentionxml: Label tree-based attention-aware deep model for high-performance extreme multi-label text classification

Reference 28

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Observation aa7c04f9-4fea-4564-8966-bd6d8116ab66 · outbound

This paper cites Use All The Labels: A Hierarchical Multi-Label Contrastive Learning Framework.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Use All The Labels: A Hierarchical Multi-Label Contrastive Learning Framework

Reference 29

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Observation 7170eca3-9d22-4af0-b379-b397999aaa1d · outbound

This paper cites Hex: Hierarchical emergence exploitation in self-supervised algorithms.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Hex: Hierarchical emergence exploitation in self-supervised algorithms

Reference 30

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Observation de7d58cd-fec4-478c-b4e4-d363913b0a23 · outbound

This paper cites Hierarchical multi-granular multi-label contrastive learning.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Hierarchical multi-granular multi-label contrastive learning

Reference 31

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Observation 87812a1c-3b0c-45a9-bfeb-c7eaafd060e6 · outbound

This paper cites Chexpert: A large chest radiograph dataset with uncertainty labels and expert comparison.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Chexpert: A large chest radiograph dataset with uncertainty labels and expert comparison

Reference 32

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This paper cites Mimic-cxr database.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Mimic-cxr database

Reference 33

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Observation d3cd1908-9293-4d61-ac39-6a6856d22284 · outbound

This paper cites Imagegcn: Multi-relational image graph convolutional networks for disease identification with chest x-rays.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Imagegcn: Multi-relational image graph convolutional networks for disease identification with chest x-rays

Reference 34

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Observation 3b60a1c0-8db2-438e-804e-0619cebf7157 · outbound

This paper cites Scalp- supervised contrastive learning for cardiopulmonary disease classification and localization in chest x-rays using patient metadata.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Scalp- supervised contrastive learning for cardiopulmonary disease classification and localization in chest x-rays using patient metadata

Reference 35

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This paper cites Representation Learning with Contrastive Predictive Coding.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Representation Learning with Contrastive Predictive Coding

Reference 36

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This paper cites Supervised contrastive learning.Advances in neural information processing systems, 33:18661–18673, 2020.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Supervised contrastive learning.Advances in neural information processing systems, 33:18661–18673, 2020

Reference 37

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Observation f7b45b59-6ad8-465d-a7b0-d08361feccfb · outbound

This paper cites Contrastive learning for multi-label classification.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Contrastive learning for multi-label classification

Reference 38

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Observation 2c3bb85b-6f98-44b6-b188-099979c0a3b5 · outbound

This paper cites An open access thyroid ultrasound image database.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging An open access thyroid ultrasound image database

Reference 39

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Observation 87c1e6c7-dc01-4419-a736-9b8dda7d7c1e · outbound

This paper cites Dataset of breast ultrasound images.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Dataset of breast ultrasound images

Reference 40

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Observation 28b07eee-c9a9-453a-b5e9-8b3559dda098 · outbound

This paper cites Deep-learning-assisted diagnosis for knee mag- netic resonance imaging: development and retrospective validation of MRNet.PLoS medicine, 15(11):e1002699,.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Deep-learning-assisted diagnosis for knee mag- netic resonance imaging: development and retrospective validation of MRNet.PLoS medicine, 15(11):e1002699,

Reference 41

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Observation 3c4d7596-4bda-4753-8458-fab3d6b80353 · outbound

This paper cites UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction.

ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

Reference 42

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ModAn-MulSupCon: Modality-and Anatomy-Aware Multi-Label Supervised Contrastive Pretraining for Medical Imaging Unresolved cited work

Reference 2018

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