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Predicting 3D Radiotherapy dose-Volume Based on Deep Learning

Intelligent Automation & Soft Computing 2024年第2期39卷 319-335页

作者： do nang toan Lam Thanh Hien Ha Manh toan Nguyen Trong Vinh Pham Trung Hieu Institute of Information Technology Vietnam Academy of Science and TechnologyHanoi10072Vietnam Faculty of Information Technology Lac Hong UniversityBien HoaDong Nai76120Vietnam

Cancer is one of the most dangerous diseaseswith *** of the principal treatments is radiotherapy by using radiation beams to destroy cancer cells and this workflow requires a lot of experience and skill from doctors and *** our study,we focused on the 3D dose prediction problem in radiotherapy by applying the deeplearning approach to computed tomography(CT)images of cancer *** image data has more complex characteristics than normal image data,and this research aims to explore the effectiveness of data preprocessing and augmentation in the context of the 3D dose prediction *** proposed four strategies to clarify our hypothesis in different aspects of applying data preprocessing and *** strategies,we trained our custom convolutional neural network model which has a structure inspired by the U-net,and residual blocks were also applied to the *** output of the network is added with a rectified linear unit(Re-Lu)function for each pixel to ensure there are no negative values,which are absurd with radiation *** experiments were conducted on the dataset of the Open Knowledge-Based Planning Challenge which was collected from head and neck cancer patients treatedwith radiation *** results of four strategies showthat our hypothesis is rational by evaluating metrics in terms of the dose-score and the dose-volume histogram score(DVH-score).In the best training cases,the dose-score is 3.08 and the DVH-score is *** addition,we also conducted a comparison with the results of another study in the same context of using the loss function.

关键词： CT image 3D dose prediction data preprocessing augmentation

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Tuberculosis Diagnosis and Visualization with a Large Vietnamese X-Ray Image Dataset

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Intelligent Automation & Soft Computing 2024年第2期39卷 281-299页

作者： Nguyen Trong Vinh Lam Thanh Hien Ha Manh toan Ngo Duc Vinh do nang toan Faculty of Information Technology Lac Hong UniversityBien HoaDong Nai76120Vietnam Institute of Information Technology Vietnam Academy of Science and TechnologyHanoi10072Vietnam Faculty of Information Technology Hanoi University of IndustryHanoi11915Vietnam

Tuberculosis is a dangerous disease to human life,and we need a lot of attempts to stop and reverse ***,in theCOVID-19 pandemic,access to medical services for tuberculosis has become very *** late detection of tuberculosis could lead to danger to patient health,even *** one of the countries heavily affected by the COVID-19 pandemic,andmany residential areas as well as hospitals have to be isolated for a long *** demands a fast and effective tuberculosis diagnosis solution to deal with the difficulty of accessingmedical services,such as an automatic tuberculosis diagnosis *** our study,aiming to build that system,we were interested in the tuberculosis diagnosis problem from the chest X-ray images of Vietnamese *** chest X-ray image is an important data type to diagnose tuberculosis,and it has also received a lot of attention from deep learning *** paper proposed a novel method for tuberculosis diagnosis and visualization using the deeplearning approach with a large Vietnamese X-ray image *** detail,we designed our custom convolutional neural network for the X-ray image classification task and then analyzed the predicted result to provide visualization as a *** prove the performance of our network model,we conducted several experiments to compare it to another study and also to evaluate it with the dataset of this *** support the implementation,we built a specific annotation system for tuberculosis under the requirements of radiologists in the Vietnam National Lung Hospital.A large experiment dataset was also from this hospital,and most of this data was for training the convolutional neural network *** experiment results were evaluated regarding sensitivity,specificity,and *** achieved high scores with a training accuracy score of 0.99,and the testing specificity and sensitivity scores were over *** on the X-ray image classification result,we visualize pr

关键词： Tuberculosis classification Vietnamese chest X-ray deep learning

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Detecting Tuberculosis from Vietnamese X-Ray Imaging Using Transfer Learning Approach

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Computers, Materials & Continua 2023年第3期74卷 5001-5016页

作者： Ha Manh toan Lam Thanh Hien Ngo Duc Vinh do nang toan Institute of Information Technology–Vietnam Academy of Science and Technology Hanoi10072Vietnam Lac Hong University Bien HoaDong Nai76120Vietnam Hanoi University of Industry Hanoi11915Vietnam

Deep learning created a sharp rise in the development of autonomous image recognition systems,especially in the case of the medical *** lung problems,tuberculosis,caused by a bacterium called Mycobacterium tuberculosis,is a dangerous disease because of its infection and *** an infected person coughs or sneezes,tiny droplets can bring pathogens to others through *** mainly damages the lungs,but it also affects any part of the ***,during the period of the COVID-19(coronavirus disease 2019)pandemic,the access to tuberculosis diagnosis and treatment has become more difficult,so early and simple detection of tuberculosis has been more and more *** our study,we focused on tuberculosis diagnosis by using the chestX-ray image,the essential input for the radiologist’s profession,and researched the effectiveness of the transfer learning approach in the case study of Vietnamese chest X-ray *** proposed four strategies to clarify our hypothesis in different ways of applying transfer learning and different training set *** also prepared a Vietnamese X-ray image dataset with the support of the VRPACS team to provide the basis for training and testing deep learning *** experiments were carried out by applying three different architectures,Alexnet,Resnet,and Densenet,on international,Vietnamese,and combined X-ray image *** training,all models were verified on a pure Vietnamese X-rays *** results show that transfer learning is suitable in the case study of Vietnamese chest X-ray images with high evaluating metrics in terms of AUC(Area under the Receiver Operating Characteristic Curve),sensitivity,specificity,and *** the best strategy,most of the scores were more than 0.93,and all AUCs were more than 0.98.

关键词： Tuberculosis diagnosis transfer learning Vietnamese chest X-ray

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