Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T14:11:55.983057Z
Paper Citation Record · LEDGER
As of 12 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 0 inbound Pith citation observations for arXiv:2411.15576.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T14:11:55.983057Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
53 of 53 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 0dd221eb-532e-4089-ab03-948f88fe3c7e · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training A simple and robust frame- work for cross-modality medical image segmentation ap- plied to vision transformers
Reference 1
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Observation 1ab891b1-b7c6-45c6-b076-7aa077d5743d · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training MONAI: An open-source framework for deep learning in healthcare
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MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Adversarial image synthesis for unpaired multi-modal cardiac data
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Observation 5f360c1f-e3db-466d-a87e-d8a9c7b831f9 · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation
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MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Generative Text-Guided 3D Vision-Language Pretraining for Unified Medical Image Segmentation
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MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training CrDoCo: Pixel-level Domain Transfer with Cross-Domain Consistency
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MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Cross-lingual lan- guage model pretraining
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MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training ResViT: Residual vision transformers for multi-modal medical image synthesis
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MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Hyperdense- net: a hyper-densely connected cnn for multi-modal im- age segmentation
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MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Unpaired multi-modal segmentation via knowledge distilla- tion
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MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Multi- modal multi-stream unet model for liver segmentation
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MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Swin unetr: Swin transformers for semantic segmentation of brain tumors in mri images
Reference 12
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Observation a2187388-cfac-45cf-a282-c9c655a3b8e7 · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Unetr: Transformers for 3d med- ical image segmentation
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MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Amos: A large-scale abdominal multi-organ benchmark for versatile medical image segmen- tation
Reference 14
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Observation 6064175a-4e26-41f0-9e14-5ba777a48088 · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Unpaired cross-modality educed distillation (cmedl) for medical image segmentation.IEEE Transactions on medical imaging, 41(5):1057–1068, 2021
Reference 15
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Observation 6f4cbb3e-1597-46d7-aa30-3e1031fdac63 · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Biobert: a pre-trained biomedical language representation model for biomedical text mining
Reference 16
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MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training AutoProSAM: Automated Prompting SAM for 3D Multi-Organ Segmentation
Reference 17
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Observation 27b62ccf-4249-400a-9b04-40ea8c3c97db · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Focalunetr: A focal transformer for boundary-aware prostate segmentation using ct images
Reference 18
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MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Towards cross-modality medical image segmentation with online mutual knowledge distillation
Reference 19
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Observation 4669c07f-4b5c-497a-bd4f-416014b5641f · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training M- flag: Medical vision-language pre-training with frozen lan- guage models and latent space geometry optimization
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Observation 6ac713be-c552-44fc-bef8-62cd3ffaec51 · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training A modality-collaborative convolution and transformer hybrid network for unpaired multi-modal medical image segmen- tation with limited annotations
Reference 21
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Observation 112ab9c9-ffe1-4b4d-8723-8cfc3a963244 · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Clip-driven universal model for organ segmentation and tumor detection
Reference 22
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Observation 27b52592-6150-4b84-a106-ad5173e12a6a · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Decoupled Weight Decay Regularization
Reference 23
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Observation 94be0a29-1f16-4ce2-ad04-c4b76b918058 · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Deep neural networks for medical image segmentation
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MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Mirror u-net: Marry- ing multimodal fission with multi-task learning for seman- tic segmentation in medical imaging
Reference 25
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Observation 20f3e7d7-cdf1-400b-9867-bc0c540fec57 · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Direct comparison of mri and x-ray ct technologies for 3d imaging of root systems in soil: potential and challenges for root trait quantification
Reference 26
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Observation 77ceefa9-ca73-4fb2-a784-cffd7e6f3d6a · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training V-net: Fully convolutional neural networks for volumetric medical image segmentation
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Observation cb43e3cb-0999-4b40-b9f1-5077ed487d4b · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Few-shot 3D Multi-modal Medical Image Segmentation using Generative Adversarial Learning
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MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training U- net: Convolutional networks for biomedical image segmen- tation
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Observation 7e5f65bd-31d2-44ea-877c-36b2c689d1a4 · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Batch Normalization Embeddings for Deep Domain Generalization
Reference 30
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Observation 3ac823e2-e333-44cc-9972-7f6bbfa6b836 · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Self-Supervised Pre-Training of Swin Transformers for 3D Medical Image Analysis
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MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Conditional con- volutions for instance segmentation
Reference 32
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Observation 85c6372c-e497-4a84-907e-25d4c83fd467 · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Tganet: Text-guided attention for improved polyp seg- mentation
Reference 33
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Observation d66d2c6a-ae6f-4ada-9f4c-a790d6415de2 · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Multi-modal learning from unpaired images: Application to multi-organ segmentation in ct and mri
Reference 34
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Observation b75cb62f-4b7f-40ef-bc9f-5e02d78d1030 · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Valindria, Nick Pawlowski, Martin Rajchl, Ioannis Lavdas, Eric O
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Observation 15ae0ae3-b7ba-4203-9236-6e91d7744bf1 · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training MedCLIP: Contrastive Learning from Unpaired Medical Images and Text
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Observation cadd9e12-3498-4c7d-979c-cfddb7c76596 · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Toward unpaired multi-modal medical image seg- mentation via learning structured semantic consistency
Reference 37
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Observation cd8521ca-8ebb-48bb-b25a-4f1e0e20ead0 · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Dillman, Nehal A
Reference 38
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Observation 113682f6-e56f-4758-bbec-277d4d56fd6e · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Dodnet: Learning to segment multi-organ and tumors from multiple partially labeled datasets
Reference 39
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MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Modality-aware mutual learning for multi-modal medical image segmenta- tion
Reference 40
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MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Cross-Task Feedback Fusion GAN for Joint MR-CT Synthesis and Segmentation of Target and Organs-At-Risk
Reference 41
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Reference 42
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Observation ffc2a1cc-2a80-4837-ab21-6366c2cf2932 · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Translating and Segmenting Multimodal Medical V olumes with Cycle- and Shape-Consistency Generative Adversarial Network, Mar
Reference 43
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MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Cross-modality medical image detection and segmentation by transfer learning of shapel priors
Reference 44
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Observation 74bfb902-8acf-4aae-b0af-fe0bd41e24bc · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Ariadne’s thread: Using text prompts to improve segmentation of infected areas from chest x-ray images
Reference 45
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Observation 52758edd-e2cf-4f8a-9063-f7ac0b7d2305 · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training A review of deep learning in medical imaging: Imaging traits, 10 technology trends, case studies with progress highlights, and future promises
Reference 46
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Observation 216d5da2-5517-4d28-9132-dc393e88e5ed · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Latent correlation representation learning for brain tumor segmentation with missing mri modalities
Reference 47
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MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training A review: Deep learning for medical image segmentation using multi- modality fusion
Reference 48
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Observation 56394eec-2f9e-4cd5-8bd7-964db83cdd13 · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Generalizable cross-modality medical image segmentation via style augmentation and dual normalization
Reference 49
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Observation 6f2bff5f-6466-4998-96e7-057241d57fa1 · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Generalizable Cross-modality Medical Image Segmen- tation via Style Augmentation and Dual Normalization
Reference 50
Source-reported events for the cited work
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Observation 0d89a572-7cb8-450a-82a6-9404a2c66602 · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Evaluation of algorithms for multi-modality whole heart segmentation: an open-access grand challenge
Reference 51
Source-reported events for the cited work
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Observation 46f0c5cf-a787-4743-8f4c-5ab9b190a46f · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Translating and Segmenting Multimodal Medical Volumes with Cycle- and Shape-Consistency Generative Adversarial Network
Reference 2019
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Observation b3bbb319-8474-48a0-b029-210a97cccdee · outbound
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training Unresolved cited work
Reference 2022
Source-reported events for the cited work
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No inbound Pith citation observations are available.