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Chuanbo Wang, Amirreza Mahbod, Isabella Ellinger, Adrian Galdran, Sandeep Gopalakrishnan, Jeffrey Niezgoda and Zeyun Yu
Wound care professionals provide proper diagnosis and treatment with heavy reliance on images and image documentation. Segmentation of wound boundaries in images is a key component of the care and diagnosis protocol since it is important to estimate the ...
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Woonghee Lee and Younghoon Kim
This study introduces a deep-learning-based framework for detecting adversarial attacks in CT image segmentation within medical imaging. The proposed methodology includes analyzing features from various layers, particularly focusing on the first layer, a...
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Shoffan Saifullah and Rafal Drezewski
Accurate medical image segmentation is paramount for precise diagnosis and treatment in modern healthcare. This research presents a comprehensive study of the efficacy of particle swarm optimization (PSO) combined with histogram equalization (HE) preproc...
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Shubin Wang, Yuanyuan Chen and Zhang Yi
The structure and function of retinal vessels play a crucial role in diagnosing and treating various ocular and systemic diseases. Therefore, the accurate segmentation of retinal vessels is of paramount importance to assist a clinical diagnosis. U-Net ha...
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Jih-Ching Chiu, Guan-Yi Lee, Chih-Yang Hsieh and Qing-You Lin
In computer vision and image processing, the shift from traditional cameras to emerging sensing tools, such as gesture recognition and object detection, addresses privacy concerns. This study navigates the Integrated Sensing and Communication (ISAC) era,...
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Claudia Angelica Rivera-Romero, Jorge Ulises Munoz-Minjares, Carlos Lastre-Dominguez and Misael Lopez-Ramirez
Identifying patient posture while they are lying in bed is an important task in medical applications such as monitoring a patient after a surgical intervention, sleep supervision to identify behavioral and physiological markers, or for bedsore prevention...
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I.A. Lozhkin,M.E. Dunaev,K.S. Zaytsev,A.A. Garmash
Pág. 109 - 117
The purpose of this work is to study the effectiveness of augmentation methods of image sets when they are insufficient in training sample of neural networks for solving semantic segmentation problems. For this purpose, the main groups of augmentation me...
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Nurhusna Najeha Amran, Khairul Salleh Basaruddin, Muhammad Farzik Ijaz, Haniza Yazid, Shafriza Nisha Basah, Nor Amalina Muhayudin and Abdul Razak Sulaiman
Spinal deformity refers to a range of disorders that are defined by anomalous curvature of the spine and may be classified as scoliosis, hypo/hyperlordosis, or hypo/hyperkyphosis. Among these, scoliosis stands out as the most common type of spinal deform...
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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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Yi Li, Nan Wang, Jinlong Li and Yu Zhang
Although the existing deblurring methods for defocused images are capable of approximately recovering clear images, they still exhibit certain limitations, such as ringing artifacts and remaining blur. Along these lines, in this work, a novel deep-learni...
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