ModDropPlusPlus
importedsoftware/moddropplusplus
Official PyTorch Implementation of ModDrop++ [MICCAI 2022 (early accept)]. A simple yet effective approach to tackle missing-modality problem for multi-modality medical imaging data.
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/han-liu/ModDropPlusPlus
- Documentation
- unknown
- Tags
- lesion-segmentation · missing-modality · mri · segmentation
- Regulatory
- unknown
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- truenetlesion-segmentation · mri · segmentation
DL tool for white matter hyperintensities segmentation
- mindGlidelesion-segmentation · segmentation
Brain MRI segmentation for multiple sclerosis — any sequence, any quality. pip install mindglide
- Breast-Cancer-Segmentationlesion-segmentation · mri
Rasa breast cancer radiology AI chatbot to help doctor segment lesions using Unity, Keras Attention UNet, LinkNet, etc
- melanoma_segmentationlesion-segmentation · segmentation
Segmentation of skin cancers on ISIC 2017 challenge dataset.
- brainstemx-fulllesion-segmentation
Why should radiologists rely on eyesight alone, when computer vision and amazing open-source processing frameworks are already available. This respository hosts the full bash-based pipeline, whilst…
- MHA-UNetlesion-segmentation
[BIBM 2025] The official code for "Only Positive Cases: 5-fold High-order Attention Interaction Model for Skin Segmentation Derived Classification".
- api.github.com/repos/han-liu/ModDropPlusPlusretrieved 2026-08-25 · via github-api
Machine-imported from GitHub search. Last push 2023-12-23, 18 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/2.json→ .entries["moddropplusplus"]
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