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20182026
most citedImage quality assessment for machine learning tasks using meta-reinforcement learning

51 citations · 178 across the 33 of their papers we have counts for

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Showing 2021Show all

5 papers · 1 filter

cs.CV2021

Adaptable image quality assessment using meta-reinforcement learning of task amenability

Shaheer U. Saeed, Yunguan Fu, Vasilis Stavrinides +8

The performance of many medical image analysis tasks are strongly associated with image data quality. When developing modern deep learning algorithms, rather than relying on subjec…

cs.CV2021

Development and evaluation of intraoperative ultrasound segmentation with negative image frames and multiple observer labels

Liam F Chalcroft, Jiongqi Qu, Sophie A Martin +8

When developing deep neural networks for segmenting intraoperative ultrasound images, several practical issues are encountered frequently, such as the presence of ultrasound frames…

eess.IV2021

Controlling False Positive/Negative Rates for Deep-Learning-Based Prostate Cancer Detection on Multiparametric MR images

Zhe Min, Fernando J. Bianco, Qianye Yang +4

Prostate cancer (PCa) is one of the leading causes of death for men worldwide. Multi-parametric magnetic resonance (mpMR) imaging has emerged as a non-invasive diagnostic tool for…

cs.LG2021★ 1 cited

Learning image quality assessment by reinforcing task amenable data selection

Shaheer U. Saeed, Yunguan Fu, Zachary M. C. Baum +6

In this paper, we consider a type of image quality assessment as a task-specific measurement, which can be used to select images that are more amenable to a given target task, such…

eess.IV2021★ 3 cited

Morphological Change Forecasting for Prostate Glands using Feature-based Registration and Kernel Density Extrapolation

Qianye Yang, Tom Vercauteren, Yunguan Fu +7

Organ morphology is a key indicator for prostate disease diagnosis and prognosis. For instance, In longitudinal study of prostate cancer patients under active surveillance, the vol…