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Lung Nodule Analysis in CT Images: Deep Learning for Segmentation and Measurement 24

Lung Nodule Analysis in CT Images: Deep Learning for Segment...

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8th International Conference on Medical and Health informatics, ICMHI 2024

作者： Li, Ai-Hsien Adams Aruperes, Cristian Daniel Lai, Yen-Jun Chien, Ting-Ying Chiu, Yen-Ling Chan, Chien-Lung Division of Cardiology Far Eastern Memorial Hospital New Taipei TaiwanGraduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan TaiwanDepartment of Computer Science and Engineering Yuan Ze University Taoyuan Taiwan TaiwanInnovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan Taiwan Department of Information Management Yuan Ze University Taoyuan Taiwan Graduate Institute of Medicine and Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan TaiwanGraduate Institute of Medicine Yuan Ze University Taoyuan Taiwan TaiwanDepartment of Medical Research Far Eastern Memorial Hospital New Taipei Taiwan Department of Radiology Far Eastern Memorial Hospital New Taipei Taiwan Department of Information Management Yuan Ze University Taoyuan Taiwan

ISBN: (纸本)9798400716874

In the realm of research, the global health challenge posed by lung cancer remains pronounced, contributing substantially to annual cancer-related fatalities. The critical imperative lies in the early identification of pulmonary nodules, frequently indicative of impending lung cancer, to enhance patient outcomes and diminish mortality rates. Computed Tomography (CT) imaging stands out as a pivotal diagnostic instrument for the timely detection of these nodules. The swift proliferation of medical imaging data has underscored the pressing necessity for precise and efficient methodologies dedicated to nodule segmentation and measurement. These approaches are crucial in assisting radiologists in their diagnostic and clinical decision-making endeavors. In this study, we introduced a thorough method for analyzing lung nodules, leveraging dataset from Far Eastern Memorial Hospital (FEMH) comprising original CT images and manually annotated ground truth masks obtained with the assistance of radiologists at FEMH. This dataset is utilized for the segmentation of nodules. We employed advanced deep learning models, specifically the U-Net architecture, identified as the optimal model through our training process. We made substantial progress in nodule segmentation, attaining an Intersection over Union (IoU) score of 0.824 and a Dice Coefficient of 0.903 for the FEMH dataset. Furthermore, our performance improved when utilizing the merged dataset comprising FEMH and Luna16, yielding an IoU score of 0.862 and a Dice Coefficient of 0.926. Luna16 has been extensively utilized in numerous studies related to nodule detection and segmentation. In the next phase of the study, the best-performing model from our segmentation phase was utilized to predict nodule masks on the merged dataset. Subsequently, we measured the size of each predicted nodule by comparing it with the size ground truth mask in millimeters. In detail, this study achieved the Pearson Correlation Coefficient (PCC) at 0.

关键词： Computerized tomography

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Evaluation of Deep Convolutional Neural Network-Based Tattoo Detection

Evaluation of Deep Convolutional Neural Network-Based Tattoo...

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Inteligencia Ambiental, Ingeniería de Software y Salud Electrónica y Móvil (AmITIC), V Congreso Internacional en

作者： E. Jiménez-Delgado C. Quesada-López A Méndez-Porras A Lara-Petitdemange J Alfaro-Velasco Graduate Program in Computer Science and Informatics University of Costa Rica Computer Engineering Department Technological Institute of Costa Rica School of Computer Science and Informatics University of Costa Rica

ISBN: (数字)9798350364538

ISBN: (纸本)9798350364545

In this study, two deep learning models for automatic tattoo detection were analyzed; a modified Convolutional Neural Network (CNN) and pre-trained ResNet-50 model. In order to achieve this, ResNet-50 uses transfer learning with fine-tuning. The purpose of this study was to evaluate the accuracy, precision, recall, F1-score, and computational efficiency of the system being considered. To augment the dataset included 1000 photos that were equally divided between those showing tattoos and those that did not show tattoos. A k-fold cross-validation approach was employed in training and testing the models. Although custom CNNs are effective, utilizing pre-trained ones like ResNet-50 can offer even better outcomes. Specifically, ResNet-50 attained a higher accuracy (0.86 compared to 0.79), precision (0.85 versus 0.78), recall (0.91 against 0.86), and F1-score (0.91 vis-a-vis 0.86) as compared to custom CNNs. In selecting these models for examination, two main motivations were considered. The first motivation is to see whether transfer learning with a pre-trained ResNet-50 model does well when compared with a customized CNN designed specifically for tattoo detection. Secondly,the intent of this study is to know what advantages can be derived from each approach and their demerits too. Furthermore, it seeks to determine if transfer learning can provide an alternative in contrast to the common CNN techniques with regards to precision and computational efficiency. In this research, two models will be evaluated in order to answer the question of what is better for tattoo detection: transfer learning or designing custom architectures.

关键词： Training Analytical models Accuracy Computational modeling Transfer learning Computer architecture Real-time systems Computational efficiency Convolutional neural networks Tuning

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Applying the MVC EA-IRPM to reporting-guidelines in medicine: A strategy that is a web system 4

Applying the MVC EA-IRPM to reporting-guidelines in medicine...

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4th IEEE EMBS International Conference on Biomedical and Health informatics, BHI 2017

作者： Letouze, Patrick De Souza, J.I.M. Silva, Valeria Martins Climaco, Glaubos Chagas, F.B. Ishihara, Joao Y. Graduate Program of Computational Modeling of Systems Universidade Federal Do Tocantins Quadra 109 Norte Avenida NS-15 Palmas77001-090 Brazil Graduate Program of Systems' Engineering and Computation - PESC Universidade Federal Do Rio de Janeiro Rio de Janeiro Brazil Department of Informatics at the Universidade Federal Do Maranh/ Ao - UFMA Brazil Faculty of Computer Science Faculdade Pitagoras Imperatriz Imperatriz Brazil Faculty of Electrical Engineering Universidade de Brasília Brasília Brazil

ISBN: (纸本)9781509041794

Reporting-Guidelines in Medicine play an important role in promoting the quality of reports in health-related research. For instance, a poorly reported research may induce misinterpretation and inappropriate clinical settings. Basically, three major issues regarding Reporting-Guidelines in Medicine has to be addressed: (1) the existence of lots of reporting guidelines covering a broad spectrum of medical research increases the difficulties when reporting a medical research because it may not be clear which guidelines are applicable, or if all related guidelines are considered;(2) most guideline developers have not described how their guidance was developed, consequently tracking guidelines and features for evaluation, or even for correcting, may be not possible;(3) few guideline developers have evaluated the effectiveness of their guidance, then the real value that the guideline brings to reporting the research is not assured. Hence, we propose a solution to these three issues based on the Model-View-Controller Evolutionary Acquisition Interdisciplinary Research Project Management (MVC EA-IRPM) that is simultaneously a strategy and a web system for the development and management of reporting guidelines. © 2017 IEEE.

关键词： Clinical research

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Lung Cancer Diseases Diagnostic Asistance Using Gray Color Analysis

Lung Cancer Diseases Diagnostic Asistance Using Gray Color A...

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International Conference on Computational Intelligence, Modelling and Simulation (CSSIM)

作者： Paulus Ford Lumban Gaol Graduate Program in Informatics Engineering Department of Computer Science Bina Nusantara University Jakarta Indonesia Bina Nusantara University Jakarta Indonesia

Errors in diagnosing the disease is a critical risk that must be faced by any person giving treatment to the hospital. Medical treatment can not always be done with perfect accuracy. Lung cancer is one of the most deadly disease that prone to misdiagnose. In general, some practitioners tend to “read” cancer in x-ray rontgen image as tumor this could be fatal. To generate a diagnose, a general practitioner use three kind of examination i.e : patient History, Radio logic examination, phisical examination. In this paper, Gray color for image indexing and retrieval are investigated. The features are derived based on the statistical distribution of Harralick feature from image sample. By utilizing the proposed invariant features, the similarity measure between query and database images provides reliable retrieval results.

关键词： Pixel Image color analysis Cancer Diseases Lungs Databases Biomedical imaging

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Sub-1 v supply nano-watt MOSFET-only threshold voltage extractor circuit 14

Sub-1 v supply nano-watt MOSFET-only threshold voltage extra...

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27th Symposium on Integrated Circuits and Systems Design, SBCCI 2014

作者： Mattia, Oscar E. Klimach, Hamilton Bampi, Sergio Microelectronics Graduate Program Federal University of Rio Grande Do sul Porto Alegre Brazil Electrical Engineering Department Federal University of Rio Grande Do sul Porto Alegre Brazil Informatics Institute Federal University of Rio Grande Do sul Porto Alegre Brazil

ISBN: (纸本)9781479968732

This work presents a self-biased MOSFET threshold voltage VT0 extractor circuit. Its working principle is based on a current-voltage relationship derived from a continuous physical model. The model is valid for any operating condition, from weak to strong inversion, and under triode or saturation regimes. The circuit is MOSFET-only (can be implemented in any standard digital process), and it operates with a power supply of less than 1 V, consuming tenths of nW. Post-layout simulation results show that the extracted VT0 has an error inferior to 1.3%, when compared to the theoretical value, for a -40 to 125°C temperature range. We present variability results from Monte Carlo simulations that support the extracting behavior of the circuit with good accuracy. The occupied silicon area is 0.0076 mm2 in a 0.13μm CMOS process. © 2014 IEEE.

关键词： Threshold voltage

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Evaluation of Various Transformer Field Conditions Using Cross-Combined Frequency Response Analysis to Identify Specific Deformity 4

Evaluation of Various Transformer Field Conditions Using Cro...

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4th International Conference on High Voltage engineering and Power Systems, ICHVEPS 2023

作者： Sutardi, Bagas Maulana Wulung, Ario Prakoso, Muhammad Helmi Pudiatmoko, Ary Abd Azis Reskiawan, M. Khayam, Umar Suwarno Pln Corporate University Graduate Program PLN-ITB Jakarta Indonesia Transformation and Ceo Office Pln Head Office Jakarta Indonesia UP3B Kalbar Pln UIP3BK Pontianak Indonesia School of Electrical Engineering and Informatics Bandung Indonesia

ISBN: (纸本)9798350318678

In HV equipment, the most critical and valuable components used is transformers. Power transformers should go through standard diagnostic tests to identify deterioration or to avoid the emergence of defects that might possibly cause severe failure. Frequency Response Analysis already proven to be a promising tool in diagnostic techniques that make use of this understanding to find such changes. FRA has so far been used to detect deformation in transformers by observing changes in the frequency response curve, despite a limited understanding of what caused the changes in the initial case. Several FRA methods have been implemented recently all around the world, primarily for transformer deformation detection and diagnosis. Nonetheless, there is now an increasing amount of research focused on determining specifically the type and degree of deformation in a transformer by looking at its FRA response curve. It is very important to refer to the guidance given in the recently published IEC, IEEE, SPLN, and CIGRE standards to ensure the accuracy of the analysis of the frequency response results. An approach for transformer diagnostics is discussed in this research by doing a comparative analysis with four study cases related to various physical phenomena and examining the cross-combined between standards and field FRA results. Four FRA measurement cases are taken from the experience in PLN, namely: Tayan (water contamination), Sanggau (transformers relocation), Sambas (rebuilding transformer foundation), and Cianjur (earthquake). The evaluation results indicate that the IEEE and IEC diagnostic standards have an assessment that is closest to the actual condition that is influenced by variations in wide band frequency measurement. © 2023 IEEE.

关键词： Power transformers

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Predicting Types of Urinary Crystals and Diameter Using Image Processing Techniques and Deep Learning Models 24

Predicting Types of Urinary Crystals and Diameter Using Imag...

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8th International Conference on Medical and Health informatics, ICMHI 2024

作者： Huang, Yu-Ju Tseng, Yi-Shiou Chen, Tzu-Jung Chien, Ting-Ying Department of Computer Science and Engineering Yuan Ze University Taoyuan City Taiwan Department of Surgery Far Eastern Memorial Hospital Graduate Institute of Medicine Yuan Ze University Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan City Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan City Taiwan

ISBN: (纸本)9798400716874

Kidney stones are primarily crystals formed from ion oversaturation in urine. Currently, the diagnosis of kidney stones involves experienced professionals manually interpreting images of urinary crystals under a microscope. In recent years, with the rapid development of artificial intelligence (AI), many researchers have proposed various methods to assist in diagnosis, hoping to improve medical quality. This study explored the application of AI in the medical field, aiming to automate the interpretation of urinary crystal images, such as red blood corpuscles (RBCs), calcium oxalate monohydrate (COM), calcium oxalate dihydrate octahedron (COD-OCT), calcium oxalate dihydrate dodecahedron (COD-DOD), debris, and others, and to use image processing techniques to classify urinary crystal types. This research is expected to assist medical personnel in quickly determining the categories of urinary crystals. Ultimately, our model achieved an F1-score of 0.93, indicating that this architecture has significant potential. © 2024 Copyright ACM.

关键词： Deep learning

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Nano-watt 0.3 v supply resistorless voltage reference with Schottky diode 7

Nano-watt 0.3 v supply resistorless voltage reference with S...

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7th IEEE Latin American Symposium on Circuits and Systems, LASCAS 2016

作者： Campana, V. Renato Klimach, Hamilton Bampi, Sergio Graduate Program on Microelectronics Federal University of Rio Grande Do sul Porto Alegre Brazil Electrical Engineering Department Federal University of Rio Grande Do sul Porto Alegre Brazil Informatics Institute Federal University of Rio Grande Do sul Porto Alegre Brazil

ISBN: (纸本)9781467378352

The analysis and design of a resistorless sub-bandgap voltage reference using Schottky diode and Low-VTo transistors is presented herein. The circuit is self-biased and works in the nano-ampere consumption range, achieving full operation at 0.3 V of supply voltage. The design is validated through post-layout simulations including process variability analysis, for a commercial 130 nm CMOS process. A voltage reference of 102.8 mV is reached under Vdd = 1.2V and 92.5 mV for VDD = 0.3V, with a temperature coefficient (TC) of 215.7 ppm/°C and 216 ppm/°C, respectively using curvature correction to improve the TC in the range from -40° C to 120° C. The current consumption is 212 nA with VDD = 1.2V at 27°C, and the chip area is 0.0068 mm2. © 2016 IEEE.

关键词： Energy gap

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Attentiveness Assessment in Learning Based on Fuzzy Logic Analysis

Attentiveness Assessment in Learning Based on Fuzzy Logic An...

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International Conference on Intelligent Systems Design and Applications (ISDA)

作者： Kuo-An Hwang Chia-Hao Yang Department of Computer Science and Information Engineering & Graduate Institute of Networking and CommunicationEngineering ChaoYang University of Technology Taiwan Graduate Institute of Informatics Doctoral program ChaoYang University of Technology Taiwan

Learner attention affects learning efficiency. However, in many classes, teachers cannot assess the degree of attention of every student. When a teacher is capable of addressing inattentive students immediately, he can avoid situations in which students are inattentive. Many studies have analyzed student attentiveness by the applying of image detection technologies. If this mechanism can be applied to in-class learning, it will help teachers keep students attentive, and reduce teacher load during class. This study mainly applies fuzzy logic analysis of student facial images when participating in class. Applying fuzzy logic can prevent erroneous judgments associated with a single term, and help teachers deal with student attentiveness.

关键词： Fuzzy logic Face detection Image analysis Image color analysis Education Eyes Design engineering Chaotic communication Image processing Face recognition

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Retracted: Implementation Method CUSUM to Determine the Accident Prone Areas in Web Based

Retracted: Implementation Method CUSUM to Determine the Acci...

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2018 Workshop on Multidisciplinary and Its Applications: Applied Mathematics, Computer Science, Information Systems, and Information Technology, WMA-Mathcomtech 2018

作者： Dinata, Rozzi Kesuma Abdullah, Dahlan Hartono, H. Erliana, Cut Ita Riasti, Berliana Kusuma Iskandar, Akbar Sari, Ifit Novita Nurmawati, N. Nanuru, Ricardo Freedom Putri, Lusi Dwi Manurung, Rosida Tiurma Sriadhi, S. Saleh, A.A. Astari, T. Khaddafi, Muammar Department of Informatics Universitas Malikussaleh Aceh Indonesia Department of Computer Science STMIK IBBI Medan Indonesia Department of Industrial Engineering Universitas Malikussaleh Aceh Indonesia Department of Informatics Universitas Sebelas Maret Surakarta Indonesia Department of Informatics STMIK AKBA Makassar Indonesia Departement Of: Social Science Education Program Post Graduate Program Universitas Kanjuruhan Malang Malang Indonesia Faculty of Industry Technique University of 45 Surabaya Indonesia Universitas Kristen Indonesia Maluku Ambon Indonesia Department of Civil Engineering Universitas Lancang Kuning Pekanbaru Indonesia Graduate Program in Scientific Psychology Universitas Kristen Maranatha Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Statistics Financial and Social Sciences Research Group Indonesia Department of Elementary School Teacher Education STKIP Citra Bangsa Aceh Utara Indonesia Department of Accounting Universitas Malikussaleh Aceh Indonesia

At the Unit Laka Lantas Polres Lhokseumawe determining accident-prone areas on roads in Lhokseumawe still using manual systems. Determination of accident-prone areas are less effective because the police Unit Laka Lantas Polres Lhokseumawe just using the data of the last year and had to repeatedly calculate manually accident-prone areas based on the number of human casualties. In this study the system implementation CUSUM method (Cummulative Summary) to determine the accident-prone areas designed using the web-based programming language PHP. In this system there are three processes to determine areas prone to accidents, the accident rate calculations based on the weighted severity, blacksite calculations using the Z-Score method for determining areas prone to accident blackspots and calculations using the CUSUM method to determine the critical points of an accident. The data used are secondary data obtained from the Police Unit Laka Lantas Polres Lhokseumawe years 2009-2013. © Published under licence by IOP Publishing Ltd.

关键词： Accidents

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