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Qianmu Xiao and Liang Zhao
Acquiring relevant, high-quality, and heterogeneous medical images is essential in various types of automated analysis, used for a variety of downstream data augmentation tasks. However, a large number of real image samples are expensive to obtain, espec...
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Mohammed Chekroun, Youssef Mourchid, Igor Bessières and Alain Lalande
The advent of the 0.35 T MR-Linac (MRIdian, ViewRay) system in radiation therapy allows precise tumor targeting for moving lesions. However, the lack of an automatic volume segmentation function in the MR-Linac?s treatment planning system poses a challen...
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A. Khuzaim Alzahrani, Ahmed A. Alsheikhy, Tawfeeq Shawly, Ahmed Azzahrani and Yahia Said
Blood cancer occurs due to changes in white blood cells (WBCs). These changes are known as leukemia. Leukemia occurs mostly in children and affects their tissues or plasma. However, it could occur in adults. This disease becomes fatal and causes death if...
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Juan Cisneros, Alain Lalande, Binnaz Yalcin, Fabrice Meriaudeau and Stephan Collins
Using a high-throughput neuroanatomical screen of histological brain sections developed in collaboration with the International Mouse Phenotyping Consortium, we previously reported a list of 198 genes whose inactivation leads to neuroanatomical phenotype...
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Emmanouil Koutoulakis, Louis Marage, Emmanouil Markodimitrakis, Leone Aubignac, Catherine Jenny, Igor Bessieres and Alain Lalande
MR-Linac is a recent device combining a linear accelerator with an MRI scanner. The improved soft tissue contrast of MR images is used for optimum delineation of tumors or organs at risk (OARs) and precise treatment delivery. Automatic segmentation of OA...
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Selene Tomassini, Haidar Anbar, Agnese Sbrollini, MHD Jafar Mortada, Laura Burattini and Micaela Morettini
The brain is the organ most studied using Magnetic Resonance (MR). The emergence of 7T scanners has increased MR imaging resolution to a sub-millimeter level. However, there is a lack of automatic segmentation techniques for 7T MR volumes. This research ...
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Rukesh Prajapati and Goo-Rak Kwon
More accurate diagnosis of brain disorders can be achieved by properly analyzing structural changes in the brain. For the quantification of change in brain structure, the segmentation task is crucial. Recently, generative adversarial networks (GAN) have ...
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Xiaoli Liu and Xiaorong Cheng
To address the problem of a low accuracy and blurred boundaries in segmenting multimodal brain tumor images using the TransBTS network, a 3D BCS_T model incorporating a channel space attention mechanism is proposed. Firstly, the TransBTS model hierarchy ...
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Raul-Ronald Galea, Laura Diosan, Anca Andreica, Loredana Popa, Simona Manole and Zoltán Bálint
Despite the promising results obtained by deep learning methods in the field of medical image segmentation, lack of sufficient data always hinders performance to a certain degree. In this work, we explore the feasibility of applying deep learning methods...
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Nur Atirah Muhadi, Ahmad Fikri Abdullah, Siti Khairunniza Bejo, Muhammad Razif Mahadi and Ana Mijic
Flood disasters are considered annual disasters in Malaysia due to their consistent occurrence. They are among the most dangerous disasters in the country. Lack of data during flood events is the main constraint to improving flood monitoring systems. Wit...
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