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Martin Paralic, Kamil Zelenak, Patrik Kamencay and Robert Hudec
The paper introduces an approach for detecting brain aneurysms, a critical medical condition, by utilizing a combination of 3D convolutional neural networks (3DCNNs) and Convolutional Long Short-Term Memory (ConvLSTM). Brain aneurysms pose a significant ...
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Junkang Qin, Xiao Wang, Dechang Mi, Qinmu Wu, Zhiqin He and Yu Tang
The study of human torso medical image segmentation is significant for computer-aided diagnosis of human examination, disease tracking, and disease prevention and treatment. In this paper, two application tasks are designed for torso medical images: the ...
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Olga Guiban, Antonello Rubini, Gianfranco Vallone, Corrado Caiazzo, Marco Di Serafino, Federica Pediconi, Laura Ballesio, Federica Trenta, Corrado De Vito, Arenta Shkelqimi, Ludovica Costanzo, Daniele Fresilli, Veronica Rizzo, Vito Cantisani and Massimo Vergine
Background: Ultrasound plays a crucial role in early diagnosis of breast cancer. The aim of this research is to evaluate the diagnostic performance of BI-RADS classification in comparison with new semi-automatic software Resona R9, Mindray, ?SmartBreast?...
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Zahra Jafari and Ebrahim Karami
The prompt and accurate diagnosis of breast lesions, including the distinction between cancer, non-cancer, and suspicious cancer, plays a crucial role in the prognosis of breast cancer. In this paper, we introduce a novel method based on feature extracti...
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Linkai Peng, Yingming Gao, Rian Bao, Ya Li and Jinsong Zhang
As an indispensable module of computer-aided pronunciation training (CAPT) systems, mispronunciation detection and diagnosis (MDD) techniques have attracted a lot of attention from academia and industry over the past decade. To train robust MDD models, t...
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