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20182021
most citedAnnotation-efficient deep learning for automatic medical image segmentation

313 citations · 559 across the 8 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

eess.IV2019★ 2 cited

Robust breast cancer detection in mammography and digital breast tomosynthesis using annotation-efficient deep learning approach

William Lotter, Abdul Rahman Diab, Bryan Haslam +10

Breast cancer remains a global challenge, causing over 1 million deaths globally in 2018. To achieve earlier breast cancer detection, screening x-ray mammography is recommended by…

eess.IV2019★ 6 cited

Validation of a deep learning mammography model in a population with low screening rates

Kevin Wu, Eric Wu, Yaping Wu +4

A key promise of AI applications in healthcare is in increasing access to quality medical care in under-served populations and emerging markets. However, deep learning models are o…

eess.IV2019★ 4 cited

Learning Cross-Modal Deep Representations for Multi-Modal MR Image Segmentation

Cheng Li, Hui Sun, Zaiyi Liu +3

Multi-modal magnetic resonance imaging (MRI) is essential in clinics for comprehensive diagnosis and surgical planning. Nevertheless, the segmentation of multi-modal MR images tend…

eess.IV2019★ 77 cited

CLCI-Net: Cross-Level fusion and Context Inference Networks for Lesion Segmentation of Chronic Stroke

Hao Yang, Weijian Huang, Kehan Qi +5

Segmenting stroke lesions from T1-weighted MR images is of great value for large-scale stroke rehabilitation neuroimaging analyses. Nevertheless, there are great challenges with th…

eess.IV2019★ 139 cited

X-Net: Brain Stroke Lesion Segmentation Based on Depthwise Separable Convolution and Long-range Dependencies

Kehan Qi, Hao Yang, Cheng Li +4

The morbidity of brain stroke increased rapidly in the past few years. To help specialists in lesion measurements and treatment planning, automatic segmentation methods are critica…