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03/27/2023
Identifying Suspicious Regions of Covid-19 by Abnormality-Sensitive Activation Mapping
This paper presents a fully-automated method for the identification of s...
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01/14/2022
Semi-automated Virtual Unfolded View Generation Method of Stomach from CT Volumes
CT image-based diagnosis of the stomach is developed as a new way of dia...
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01/09/2022
COVID-19 Infection Segmentation from Chest CT Images Based on Scale Uncertainty
This paper proposes a segmentation method of infection regions in the lu...
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01/09/2022
Lung infection and normal region segmentation from CT volumes of COVID-19 cases
This paper proposes an automated segmentation method of infection and no...
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08/05/2019
Precise Estimation of Renal Vascular Dominant Regions Using Spatially Aware Fully Convolutional Networks, Tensor-Cut and Voronoi Diagrams
This paper presents a new approach for precisely estimating the renal va...
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06/06/2018
A multi-scale pyramid of 3D fully convolutional networks for abdominal multi-organ segmentation
Recent advances in deep learning, like 3D fully convolutional networks (...
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03/23/2018
Deep learning and its application to medical image segmentation
One of the most common tasks in medical imaging is semantic segmentation...
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03/14/2018
An application of cascaded 3D fully convolutional networks for medical image segmentation
Recent advances in 3D fully convolutional networks (FCN) have made it fe...
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01/18/2018
On the influence of Dice loss function in multi-class organ segmentation of abdominal CT using 3D fully convolutional networks
Deep learning-based methods achieved impressive results for the segmenta...
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11/17/2017