ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training | Paper Citation Record

Observation 9b7cc976-588b-44bc-88a6-98d8c799a8da · outbound

This paper cites Simcrop: Radiograph representation learning with similarity-driven cross-granularity pre-training,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Simcrop: Radiograph representation learning with similarity-driven cross-granularity pre-training,

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This paper cites Unimiss+: Universal medical self-supervised learn- ing from cross-dimensional unpaired data,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Unimiss+: Universal medical self-supervised learn- ing from cross-dimensional unpaired data,

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This paper cites Medical image segmentation review: The success of u-net,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Medical image segmentation review: The success of u-net,

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This paper cites Visionunite: A vision-language foundation model for ophthalmology enhanced with clinical knowledge,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Visionunite: A vision-language foundation model for ophthalmology enhanced with clinical knowledge,

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This paper cites Pathway-aware multimodal transformer (pamt): Integrating pathological image and gene expression for inter- pretable cancer survival analysis,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Pathway-aware multimodal transformer (pamt): Integrating pathological image and gene expression for inter- pretable cancer survival analysis,

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This paper cites A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises,

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This paper cites Minimizing estimated risks on unlabeled data: A new formulation for semi-supervised medical image segmentation,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Minimizing estimated risks on unlabeled data: A new formulation for semi-supervised medical image segmentation,

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This paper cites Deep transfer learning based classification model for covid-19 disease,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Deep transfer learning based classification model for covid-19 disease,

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Observation e9a9d5bd-4838-47db-84e0-299f9c1eab0c · outbound

This paper cites Recent advances and clinical applications of deep learning in medical image analysis,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Recent advances and clinical applications of deep learning in medical image analysis,

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This paper cites Diagnose like a radiologist: Hybrid neuro- probabilistic reasoning for attribute-based medical image diag- nosis,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Diagnose like a radiologist: Hybrid neuro- probabilistic reasoning for attribute-based medical image diag- nosis,

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Observation 676dd4f3-d243-4e0e-94ea-7dc96b1274a6 · outbound

This paper cites Homeomorphism prior for false positive and nega- tive problem in medical image dense contrastive representation learning,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Homeomorphism prior for false positive and nega- tive problem in medical image dense contrastive representation learning,

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This paper cites Generalized radiograph representation learn- ing via cross-supervision between images and free-text radiology reports,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Generalized radiograph representation learn- ing via cross-supervision between images and free-text radiology reports,

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This paper cites Knowledge- enhanced visual-language pre-training on chest radiology im- ages,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Knowledge- enhanced visual-language pre-training on chest radiology im- ages,

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Observation 98c4a3d7-5ee5-485a-a70f-c4786eaf2b7d · outbound

This paper cites Towards generalist foundation model for radiology by leveraging web-scale 2d&3d medical data,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Towards generalist foundation model for radiology by leveraging web-scale 2d&3d medical data,

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This paper cites A unified visual information preservation framework for self-supervised pre-training in medical image analysis,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training A unified visual information preservation framework for self-supervised pre-training in medical image analysis,

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This paper cites A medical multimodal large language model for future pandemics,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training A medical multimodal large language model for future pandemics,

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This paper cites Abdomenct-1k: Is abdominal organ segmentation a solved problem?.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Abdomenct-1k: Is abdominal organ segmentation a solved problem?

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Observation dd8317ba-8bbb-4d6f-bcd7-18388815536e · outbound

This paper cites Development of a large-scale medical visual question-answering dataset,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Development of a large-scale medical visual question-answering dataset,

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This paper cites Large-scale long-tailed disease diagnosis on radiology images,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Large-scale long-tailed disease diagnosis on radiology images,

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This paper cites Medical multimodal multitask foundation model for lung cancer screening,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Medical multimodal multitask foundation model for lung cancer screening,

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This paper cites Hi-end-mae: Hierarchical encoder-driven masked autoencoders are stronger vision learners for medical image segmentation,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Hi-end-mae: Hierarchical encoder-driven masked autoencoders are stronger vision learners for medical image segmentation,

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This paper cites Contrastive learning of medical visual repre- sentations from paired images and text,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Contrastive learning of medical visual repre- sentations from paired images and text,

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This paper cites Gloria: A multimodal global-local repre- sentation learning framework for label-efficient medical image recognition,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Gloria: A multimodal global-local repre- sentation learning framework for label-efficient medical image recognition,

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This paper cites Multi-granularity cross-modal align- ment for generalized medical visual representation learning,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Multi-granularity cross-modal align- ment for generalized medical visual representation learning,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training MedCLIP: Contrastive learning from unpaired medical images and text,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Medklip: Medical knowledge enhanced language- image pre-training,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Expert-level detection of pathologies from unan- notated chest x-ray images via self-supervised learning,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Advancing radiograph representation learning with masked record modeling,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Mlip: Enhancing medical visual representation with divergence encoder and knowledge-guided contrastive learn- ing,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Enhancing representation in radiography- reports foundation model: A granular alignment algorithm using masked contrastive learning,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Ecamp: Entity-centered context-aware medical vision language pre-training,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Efficient medical vision-language alignment through adapting masked vision models,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Bootstrapping chest ct image understanding by distilling knowledge from x-ray expert models,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Merlin: a computed tomography vision– language foundation model and dataset,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Large-scale 3d medical image pre-training with geometric context priors,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Generalist foundation models from a mul- timodal dataset for 3d computed tomography,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Machine-learning-based multiple abnor- mality prediction with large-scale chest computed tomography volumes,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training BIMCV COVID-19+: a large annotated dataset of RX and CT images from COVID-19 patients

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Large-scale and fine-grained vision-language pre- training for enhanced ct image understanding,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Boosting vision semantic density with anatomy normality modeling for medical vision-language pre-training,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training arXiv preprint arXiv:2404.15272 (2024)

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training M3D: Advancing 3D Medical Image Analysis with Multi-Modal Large Language Models

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training T3d: Advancing 3d medical vision-language pre- training by learning multi-view visual consistency,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Radzero3d: Bridging self-supervised video models and medical vision-language alignment for zero-shot chest ct interpretation,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Large-vocabulary segmentation for medical im- ages with text prompts,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Totalsegmentator: robust segmentation of 104 anatomic structures in ct images,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Towards scalable language-image pre-training for 3d medical imaging,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Multi-modal masked autoencoders for medical vision-and-language pre-training,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Learning transferable visual models from natural language supervision,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Scaling up visual and vision-language representation learning with noisy text supervision,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training CoCa: Contrastive Captioners are Image-Text Foundation Models

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Grounded language-image pre-training,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Scaling language-image pre-training via masking,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Flamingo: a visual language model for few- shot learning,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Visual instruction tuning,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Sigmoid loss for language image pre-training,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Vl-bert: Pre-training of generic visual-linguistic representations,

Reference 59

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Beit: Bert pre-training of image transformers,

Reference 60

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Flava: A foundational language and vision alignment model,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Image as a foreign language: Beit pretraining for vision and vision-language tasks,

Reference 62

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Valor: Vision-audio-language omni-perception pre- training model and dataset,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Unsupervised pre-training with language-vision prompts for low-data instance segmentation,

Reference 64

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This paper cites Mimic-cxr, a de-identified publicly available database of chest radiographs with free-text reports,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Mimic-cxr, a de-identified publicly available database of chest radiographs with free-text reports,

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This paper cites Eva-x: A foundation model for general chest x- ray analysis with self-supervised learning,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Eva-x: A foundation model for general chest x- ray analysis with self-supervised learning,

Reference 66

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This paper cites Med-unic: Unifying cross-lingual medical vision- language pre-training by diminishing bias,.

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Rethinking masked image modeling for medical image representation,

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This paper cites Voco: A simple-yet-effective volume contrastive learning framework for 3d medical image analysis,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Voco: A simple-yet-effective volume contrastive learning framework for 3d medical image analysis,

Reference 69

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Reference 70

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This paper cites Enhancing the vision–language foundation model with key semantic knowledge-emphasized report refine- ment,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Enhancing the vision–language foundation model with key semantic knowledge-emphasized report refine- ment,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Imitate: Clinical prior guided hierarchical vision- language pre-training,

Reference 72

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Multi-grained vision-and-language model for medical image and text alignment,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Prior: Prototype representation joint learning from medical images and reports,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training G2d: From global to dense radiography representa- tion learning via vision-language pre-training,

Reference 76

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training X-ray computed tomography,

Reference 77

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Geometric visual similarity learning in 3d medical image self-supervised pre-training,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Unified medical image pre-training in language- guided common semantic space,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Mg-3d: Multi-grained knowledge-enhanced vision- language pre-training for 3d medical image analysis,

Reference 80

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training An image is worth 16x16 words: Trans- formers for image recognition at scale,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Bert: Pre-training of deep bidirectional transform- ers for language understanding,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Masked autoencoders are scalable vision learners,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Self pre-training with masked autoencoders for medical image classification and segmentation,

Reference 85

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training The medical segmentation decathlon,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Rapid artificial intelligence solutions in a pan- demic—the covid-19-20 lung ct lesion segmentation challenge,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Segthor: Segmentation of thoracic organs at risk in ct images,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training A new dataset of computed-tomography angiography images for computer-aided detection of pulmonary embolism,

Reference 90

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Miccai multi-atlas labeling beyond the cranial vault–workshop and challenge,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Deep learning techniques for automatic mri cardiac multi-structures segmentation and diagnosis: is the prob- lem solved?

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This paper cites Work like a doctor: Unifying scan localizer and dynamic generator for automated computed tomography report generation,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Work like a doctor: Unifying scan localizer and dynamic generator for automated computed tomography report generation,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: the luna16 challenge,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training INSPECT: A Multimodal Dataset for Pulmonary Embolism Diagnosis and Prognosis

Reference 95

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Study of thoracic ct in covid-19: the stoic project,

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ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Development of a large-scale grounded vision language dataset for chest ct analysis,

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This paper cites The rsna pulmonary embolism ct dataset,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training The rsna pulmonary embolism ct dataset,

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This paper cites Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach,

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This paper cites Towards data-efficient learning: A benchmark for covid-19 ct lung and infection segmentation,.

ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training Towards data-efficient learning: A benchmark for covid-19 ct lung and infection segmentation,

Reference 100

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