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20182022
most citedMONAI: An open-source framework for deep learning in healthcare

452 citations · 556 across the 14 of their papers we have counts for

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14 papers · 1 filter

eess.IV20222 cited

Automated head and neck tumor segmentation from 3D PET/CT

Andriy Myronenko, Md Mahfuzur Rahman Siddiquee, Dong Yang +2

Head and neck tumor segmentation challenge (HECKTOR) 2022 offers a platform for researchers to compare their solutions to segmentation of tumors and lymph nodes from 3D CT and PET…

eess.IV20222 cited

Automated segmentation of intracranial hemorrhages from 3D CT

Md Mahfuzur Rahman Siddiquee, Dong Yang, Yufan He +2

Intracranial hemorrhage segmentation challenge (INSTANCE 2022) offers a platform for researchers to compare their solutions to segmentation of hemorrhage stroke regions from 3D CTs…

eess.IV20223 cited

Automated ischemic stroke lesion segmentation from 3D MRI

Md Mahfuzur Rahman Siddique, Dong Yang, Yufan He +2

Ischemic Stroke Lesion Segmentation challenge (ISLES 2022) offers a platform for researchers to compare their solutions to 3D segmentation of ischemic stroke regions from 3D MRIs.…

eess.IV20211 cited

Accounting for Dependencies in Deep Learning Based Multiple Instance Learning for Whole Slide Imaging

Andriy Myronenko, Ziyue Xu, Dong Yang +2

Multiple instance learning (MIL) is a key algorithm for classification of whole slide images (WSI). Histology WSIs can have billions of pixels, which create enormous computational…

eess.IV20212 cited

Redundancy Reduction in Semantic Segmentation of 3D Brain Tumor MRIs

Md Mahfuzur Rahman Siddiquee, Andriy Myronenko

Another year of the multimodal brain tumor segmentation challenge (BraTS) 2021 provides an even larger dataset to facilitate collaboration and research of brain tumor segmentation…

eess.IV20211 cited

Federated Whole Prostate Segmentation in MRI with Personalized Neural Architectures

Holger R. Roth, Dong Yang, Wenqi Li +5

Building robust deep learning-based models requires diverse training data, ideally from several sources. However, these datasets cannot be combined easily because of patient privac…