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László Szilágyi and Levente Kovács
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Hyunkyung Shin, Hyeonung Shin, Wonje Choi, Jaesung Park, Minjae Park, Euiyul Koh and Honguk Woo
The automatic analysis of medical data and images to help diagnosis has recently become a major area in the application of deep learning. In general, deep learning techniques can be effective when a large high-quality dataset is available for model train...
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Andreea Bianca Popescu, Ioana Antonia Taca, Anamaria Vizitiu, Cosmin Ioan Nita, Constantin Suciu, Lucian Mihai Itu and Alexandru Scafa-Udriste
Deep learning (DL)-based algorithms have demonstrated remarkable results in potentially improving the performance and the efficiency of healthcare applications. Since the data typically needs to leave the healthcare facility for performing model training...
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Jayashree Moorthy and Usha Devi Gandhi
Deep learning techniques have rapidly become important as a preferred method for evaluating medical image segmentation. This survey analyses different contributions in the deep learning medical field, including the major common issues published in recent...
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Nasrin Bayat, Diane D. Davey, Melanie Coathup and Joon-Hyuk Park
Accurate and robust human immune system assessment through white blood cell evaluation require computer-aided tools with pathologist-level accuracy. This work presents a multi-attention leukocytes subtype classification method by leveraging fine-grained ...
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Mustafa Kara, Zeynep Öztürk, Sergin Akpek and Aysegül Turupcu
Advancements in deep learning and availability of medical imaging data have led to the use of CNN-based architectures in disease diagnostic assisted systems. In spite of the abundant use of reverse transcription-polymerase chain reaction-based tests in C...
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Minh-Trieu Tran, Soo-Hyung Kim, Hyung-Jeong Yang and Guee-Sang Lee
Distorted medical images can significantly hamper medical diagnosis, notably in the analysis of Computer Tomography (CT) images and organ segmentation specifics. Therefore, improving diagnostic imagery accuracy and reconstructing damaged portions are imp...
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Lourdes Duran-Lopez, Juan Pedro Dominguez-Morales, Jesús Corral-Jaime, Saturnino Vicente-Diaz and Alejandro Linares-Barranco
This work could be used to aid radiologists in the screening process, contributing to the fight against COVID-19.
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Sami Bourouis, Roobaea Alroobaea, Saeed Rubaiee and Anas Ahmed
Accurate medical images analysis plays a vital role for several clinical applications. Nevertheless, the immense and complex data volume to be processed make difficult the design of effective algorithms. The first aim of this paper is to examine this are...
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Weibo Song
The proper evaluation of heart health requires professional medical experience. Therefore, in clinical diagnosis practice, the development direction is to reduce the high dependence of the diagnosis process on medical experience and to more effectively i...
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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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Mathilde Merle, Florent Collot, Julien Castelneau, Pauline Migerditichan, Mehdi Juhoor, Buntheng Ly, Valery Ozenne, Bruno Quesson, Nejib Zemzemi, Yves Coudière, Pierre Jaïs, Hubert Cochet and Maxime Sermesant
The tremendous advancement of cardiac imaging methods, the substantial progress in predictive modelling, along with the amount of new investigative multimodalities, challenge the current technologies in the cardiology field. Innovative, robust and multim...
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Giorgia Fiori, Fabio Fuiano, Andrea Scorza, Jan Galo, Silvia Conforto and Salvatore Andrea Sciuto
The present work is aimed at providing a novel image analysis-based method for the maximum depth of penetration (DOP) measurement in Quality Assessment (QA) of medical ultrasound systems.
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Ruslan Vafin,Rashit Nasyrov,Rustem Zulkarneev
Pág. 21 - 28
Currently, one of the promising areas in medicine is personalized medicine, which allows selecting the optimal treatment for each individual patient. Within the framework of the national program "Digital Economy of the Russian Federation", artificial int...
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Ruslan Vafin,Rashit Nasyrov,Rustem Zulkarneev
Pág. 21 - 28
Currently, one of the promising areas in medicine is personalized medicine, which allows selecting the optimal treatment for each individual patient. Within the framework of the national program "Digital Economy of the Russian Federation", artificial int...
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S.G. Magomedov
Pág. 84 - 89
Nowadays personal medical devices play an increasingly important role in health care ecosystems as equipment for life support of patients. And the malicious software and protocols interacting with this equipment cause more and more interest. Any data tra...
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Mihai-Virgil Nichita, Maria-Alexandra Paun, Vladimir-Alexandru Paun and Viorel-Puiu Paun
This paper introduces an AI model designed for the diagnosis and monitoring of the SARS-CoV-2 virus. The present artificial intelligence (AI) model founded on the machine learning concept was created for the identification/recognition, keeping under obse...
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Thomas P. Oghalai, Ryan Long, Wihan Kim, Brian E. Applegate and John S. Oghalai
Optical Coherence Tomography (OCT) is a light-based imaging modality that is used widely in the diagnosis and management of eye disease, and it is starting to become used to evaluate for ear disease. However, manual image analysis to interpret the anatom...
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Christian Mata, Josep Munuera, Alain Lalande, Gilberto Ochoa-Ruiz and Raul Benitez
In the field of medical imaging, the division of an image into meaningful structures using image segmentation is an essential step for pre-processing analysis. Many studies have been carried out to solve the general problem of the evaluation of image seg...
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Pedro Celard, Adrián Seara Vieira, José Manuel Sorribes-Fdez, Eva Lorenzo Iglesias and Lourdes Borrajo
In this study, we propose a novel Temporal Development Generative Adversarial Network (TD-GAN) for the generation and analysis of videos, with a particular focus on biological and medical applications. Inspired by Progressive Growing GAN (PG-GAN) and Tem...
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