Article
Automation & Control Systems
Andrii Hrechuk, Mikael Horndahl, Fredrik Schultheiss
Summary: This paper develops a research solution for automatic analysis of the hole quality in drilled fiber-reinforced materials. The proposed solution includes a vacuum table, robot arm with high-speed camera, developed lightning systems, and Image Processing algorithms. The results show that the developed solution can achieve an efficiency of 5 seconds per hole including drilling and full cycle of measurements, with a measurement error of 1-3%.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Article
Optics
Bin Liang, Dongdong Weng, Ziqi Tu, Le Luo, Jie Hao
Summary: This study addresses the issue of specular components in face images by introducing a high-resolution Asian face dataset based on polarization characteristics, and developing a multi-task GAN approach for joint specular removal and intrinsic decomposition. Experimental results demonstrate the significant performance advantage of our method in face image processing.
Article
Chemistry, Analytical
Laura Nicolas-Saenz, Agapito Ledezma, Javier Pascau, Arrate Munoz-Barrutia
Summary: Classifying pixels according to color and segmenting areas are necessary steps in computer vision tasks. The challenges in properly classifying pixels based on color lie in the differences between human perception, linguistic terminology, and digital representation. To address this, a novel method combining geometric analysis, color theory, fuzzy color theory, and multi-label systems was proposed. The method shows accuracy in color analysis and provides a standardized alternative for color naming recognizable by both humans and machines.
Article
Computer Science, Information Systems
Shuang Wang, Jingyu Liu, Shuqi Liu, Boshi Yin, Jian Jiang, Jing Lan
Summary: The research aims to investigate the factors affecting color harmony from perception to cognition and construct a mathematical model for quantitative analysis. It is found that color harmony is influenced not only by objective factors, but also by subjective factors.
Article
Psychology, Multidisciplinary
Feng Wang, Jifeng Xu, Hanning Zhang, Jun Yin
Summary: This study aims to accurately discover the color preferences and image positioning of different female groups in China, in order to establish a color reference system suitable for beauty product packaging. Through questionnaire surveys, color classification, and analysis of middle-aged rural women, valuable information and guidance for future beauty packaging designs can be provided.
FRONTIERS IN PSYCHOLOGY
(2021)
Article
Chemistry, Applied
Simon Smolders, Huibo Sheng, Matthew P. P. Mower, Aditi Potdar, Jan Dijkmans
Summary: Pharmaceutical R&D employs data-driven approaches and specialized process analytical technology tools for efficient and reliable process development. This article demonstrates the ease of using cameras to provide data in various unit operations. Color analysis is shown to be a valuable method for monitoring reaction progress, color removal, solubility determination, nucleation detection, filtration curves, and material color.
ORGANIC PROCESS RESEARCH & DEVELOPMENT
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Oona Rainio, Chunlei Han, Jarmo Teuho, Sergey V. Nesterov, Vesa Oikonen, Sauli Piirola, Timo Laitinen, Marko Tattalainen, Juhani Knuuti, Riku Klen
Summary: Carimas is a versatile tool for processing medical imaging data, allowing visualization, analysis, and modeling of various medical images in research. Originally designed for positron emission tomography data, it has expanded to include other tomography imaging modalities like computed tomography and magnetic resonance imaging. Carimas excels in analyzing three- and four-dimensional image data and creating polar maps for cardiac perfusion modeling.
JOURNAL OF DIGITAL IMAGING
(2023)
Article
Computer Science, Artificial Intelligence
Chao Fan, Kai Hu, Yuyi Yuan, Yu Li
Summary: With the development of artificial intelligence and high-performance computing equipment, new technologies have greatly impacted medical image research. Traditional literature review methods are insufficient to keep up with global research trends, so a data-driven analysis was used to characterize these trends. The analysis revealed that medical image research is on an upward trend, with advancements in deep learning playing a significant role. The most influential journals, authors, and countries were identified, highlighting the importance of interdisciplinary collaborations in this field.
Review
Materials Science, Textiles
Zhouqiang Zhang, Jianghao Liu, Jie Zan, Zhenhua Wang
Summary: In this paper, a color difference detection method for printed fabrics based on image segmentation and image registration is proposed. The method improves the accuracy of detection and calculates the color difference value using the CIEDE2000 color difference formula.
TEXTILE RESEARCH JOURNAL
(2023)
Review
Chemistry, Analytical
Muhammad Waqas Nadeem, Hock Guan Goh, Muzammil Hussain, Soung-Yue Liew, Ivan Andonovic, Muhammad Adnan Khan
Summary: Deep learning has been widely applied in various fields, especially in image processing and bioinformatics. This article provides a comprehensive review of the development of deep learning in the analysis of diabetic retinopathy, including screening, segmentation, prediction, classification, and validation. It critically analyzes the relevant techniques, highlights their advantages and limitations, and identifies research gaps and future challenges.
Article
Computer Science, Information Systems
S. M. A. Sharif, Rizwan Ali Naqvi, Mithun Biswas, Woong-Kee Loh
Summary: This study proposes an end-to-end learning strategy to enhance the perceptual quality of medical images, comprehensively addressing contrast correction, luminance correction, denoising, etc. Experimental results show that the proposed method outperforms existing methods in terms of peak signal-to-noise ratio (PSNR) and DeltaE metrics.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2022)
Review
Computer Science, Information Systems
Sajid Ullah Khan, Mir Ahmad Khan, Muhammad Azhar, Faheem Khan, Youngmoon Lee, Muhammad Javed
Summary: Medical imaging has been widely used in diagnosing various disorders, but the challenge lies in accurate disease identification and improved therapies. Multi modal image fusion (MMIF) aims to combine complementary information from different imaging modalities to improve the quality and clear assessment of medical related problems. This review provides a detailed overview of medical imaging modalities, multimodal medical image databases, MMIF steps/rules, methods, performance evaluation, and future directions. It is expected to be valuable in developing more effective medical image fusion methods for clinical diagnosis.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2023)
Article
Mathematics, Applied
Khalid M. Hosny, Mohamed M. Darwish
Summary: This paper defines a new method, called fractional-order quaternion orthogonal shifted Gegenbauer moments (FrQSGMs), for color image analysis and recognition. The proposed method does not require image mapping or interpolation and exhibits geometric transformation invariance.
APPLIED MATHEMATICS AND COMPUTATION
(2022)
Article
Neurosciences
Hao Guan, Mingxia Liu
Summary: Domain adaptation is an important technique in machine learning-based medical data analysis to reduce distribution differences between different datasets. The Domain Adaptation Toolbox for Medical data analysis (DomainATM) is an open-source software package implemented in MATLAB, offering a collection of popular data adaptation algorithms for medical image analysis. It provides researchers with the capability to perform fast feature-level and image-level adaptation, visualization, and performance evaluation of adaptation methods. Users can also develop and test their own adaptation methods through scripting, enhancing the utility and extensibility of DomainATM. The software, source code, and manual are available online.
Article
Computer Science, Information Systems
Matina C. H. Zerva, Vasileios Christou, Nikolaos Giannakeas, Alexandros T. Tzallas, Lisimachos P. Kondi
Summary: This paper proposes a novel and improved medical image compression method based on color wavelet difference reduction. The proposed method selects the optimum quantity of color images that present the highest similarity in the spatial and temporal domain to encode images with large spatiotemporal coherence. The evaluation results show a remarkably high perceptual quality of the medical image, with a PSNR improvement of up to 22.65 dB compared to JPEG 2000 and up to 10.33dB compared to a method utilizing DWT.
Article
Mathematical & Computational Biology
K. N. Manjunath, P. C. Siddalingaswamy, K. Gopalakrishna Prabhu
JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS
(2016)
Article
Engineering, Biomedical
K. N. Manjunath, P. C. Siddalingaswamy, G. K. Prabhu
INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY
(2017)
Article
Biochemistry & Molecular Biology
Siddeshappa Nandish, Gopalakrishna Prabhu, Kadavigere V. Rajagopal
BIOMEDICAL JOURNAL
(2017)
Review
Engineering, Biomedical
Sameena Pathan, K. Gopalakrishna Prabhu, P. C. Siddalingaswamy
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2018)
Review
Oncology
Kanabagatte Nanjundappa Manjunath, Prabhu Karkala Gopalakrishna, Puttappa Chandrappa Siddalingaswamy
ASIAN PACIFIC JOURNAL OF CANCER PREVENTION
(2014)
Article
Health Care Sciences & Services
H. Anitha, G. K. Prabhu, A. K. Karunakar
JOURNAL OF MEDICAL SYSTEMS
(2014)
Article
Multidisciplinary Sciences
Vijendra Prabhu, Satish B. S. Rao, Edward Mark Fernandes, Anuradha C. K. Rao, Keerthana Prasad, Krishna K. Mahato
Article
Health Care Sciences & Services
Roopa B. Hegde, Keerthana Prasad, Harishchandra Hebbar, Brij Mohan Kumar Singh
JOURNAL OF MEDICAL SYSTEMS
(2019)
Article
Radiology, Nuclear Medicine & Medical Imaging
Roopa B. Hegde, Keerthana Prasad, Harishchandra Hebbar, Brij Mohan Kumar Singh, I Sandhya
JOURNAL OF DIGITAL IMAGING
(2020)
Article
Radiology, Nuclear Medicine & Medical Imaging
Vidya Kudva, Keerthana Prasad, Shyamala Guruvare
JOURNAL OF DIGITAL IMAGING
(2020)
Review
Computer Science, Interdisciplinary Applications
K. T. Navya, Keerthana Prasad, Brij Mohan Kumar Singh
Summary: This paper presents a review of the methods used to analyze the characteristics of red blood cells from PBS images using image processing techniques. The methods are categorized based on approaches such as RBC segmentation, RBC classification and detection of anemia, and classification of anemia. The need for an inexpensive, automatic and robust technique to detect RBC disorders is emphasized.
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
(2022)
Article
Computer Science, Information Systems
R. Rashmi, Keerthana Prasad, Chethana Babu K. Udupa, V Shwetha
Article
Computer Science, Artificial Intelligence
Sameena Pathan, P. C. Siddalingaswamy, K. Gopalakrishna Prabhu
PROGRESS IN ARTIFICIAL INTELLIGENCE
(2018)
Correction
Dermatology
Naveen Kumar, Pramod Kumar, Satheesha Nayak Badagabettu, Keerthana Prasad, Ranjini Kudva, Coimbatore Vasudevarao Raghuveer
DERMATOLOGY RESEARCH AND PRACTICE
(2015)
Article
Dermatology
Naveen Kumar, Pramod Kumar, Satheesha Nayak Badagabettu, Keerthana Prasad, Ranjini Kudva, Coimbatore Vasudevarao Raghuveer
DERMATOLOGY RESEARCH AND PRACTICE
(2014)
Article
Computer Science, Interdisciplinary Applications
Alireza Karimi, Reza Razaghi, Siddharth Daniel D'costa, Saeed Torbati, Sina Ebrahimi, Seyed Mohammadali Rahmati, Mary J. Kelley, Ted S. Acott, Haiyan Gong
Summary: This study investigated the biomechanical properties of the conventional aqueous outflow pathway using fluid-structure interaction. The results showed that the distribution of aqueous humor wall shear stress within this pathway is not uniform, which may contribute to our understanding of the underlying selective mechanisms.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Robert V. Bergen, Jean-Francois Rajotte, Fereshteh Yousefirizi, Arman Rahmim, Raymond T. Ng
Summary: This article introduces a 3D generative model called TrGAN, which can generate medical images with important features and statistical properties while protecting privacy. By evaluating through a membership inference attack, the fidelity, utility, and privacy trade-offs of the model were studied.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Hoda Mashayekhi, Mostafa Nazari, Fatemeh Jafarinejad, Nader Meskin
Summary: In this study, a novel model-free adaptive control method based on deep reinforcement learning (DRL) is proposed for cancer chemotherapy drug dosing. The method models the state variables and control action in their original infinite spaces, providing a more realistic solution. Numerical analysis shows the superior performance of the proposed method compared to the state-of-the-art RL-based approach.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Hao Sun, Bao Li, Liyuan Zhang, Yanping Zhang, Jincheng Liu, Suqin Huang, Xiaolu Xi, Youjun Liu
Summary: In cases of moderate stenosis in the internal carotid artery, the A1 segment of the anterior cerebral artery or the posterior communicating artery within the Circle of Willis may show a hemodynamic environment with high OSI and low TAWSS, increasing the risk of atherosclerosis development and stenosis in the CoW.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Ilaria Toniolo, Paola Pirini, Silvana Perretta, Emanuele Luigi Carniel, Alice Berardo
Summary: This study compared the outcomes of endoscopic sleeve gastroplasty (ESG) and laparoscopic sleeve gastrectomy (LSG) in weight loss surgery using computational models of specific patients. The results showed significant differences between the two procedures in terms of stomach volume reduction and mechanical stimulation. A predictive model was proposed to support surgical planning and estimation of volume reduction after ESG.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Chun-You Chen, Ya-Lin Chen, Jeremiah Scholl, Hsuan-Chia Yang, Yu-Chuan (Jack) Li
Summary: This study evaluated the overall performance of a machine learning-based CDSS (MedGuard) in triggering clinically relevant alerts and intercepting inappropriate drug errors and LASA drug errors. The results showed that MedGuard has the ability to improve patients' safety by triggering clinically valid alerts.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Lingzhi Tang, Xueqi Wang, Jinzhu Yang, Yonghuai Wang, Mingjun Qu, HongHe Li
Summary: In this paper, a dynamical local feature fusion net for automatically recognizing aortic valve calcification (AVC) from echocardiographic images is proposed. The network segments high-echo areas and adjusts the selection of local features to better integrate global and local semantic representations. Experimental results demonstrate the effectiveness of the proposed approach.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
You-Lei Fu, Wu Song, Wanni Xu, Jie Lin, Xuchao Nian
Summary: This study investigates the combination of surface electromyographic signals (sEMG) and deep learning-based CNN networks to study the interaction between humans and products and the impact on body comfort. It compares the advantages and disadvantages of different CNN networks and finds that DenseNet has unique advantages over other algorithms in terms of accuracy and ease of training, while mitigating issues of gradient disappearance and model degradation.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Moritz Rempe, Florian Mentzel, Kelsey L. Pomykala, Johannes Haubold, Felix Nensa, Kevin Kroeninger, Jan Egger, Jens Kleesiek
Summary: In this study, a deep learning-based skull stripping algorithm for MRI was proposed, which works directly in the complex valued k-space and preserves the phase information. The results showed that the algorithm achieved similar results to the ground truth, with higher accuracy in the slices above the eye region. This approach not only preserves valuable information for further diagnostics, but also enables immediate anonymization of patient data before being transformed into the image domain.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Ziyang Chen, Laura Cruciani, Elena Lievore, Matteo Fontana, Ottavio De Cobelli, Gennaro Musi, Giancarlo Ferrigno, Elena De Momi
Summary: In this paper, a deep learning-based approach is proposed to recover 3D information of intra-operative scenes, which can enhance the safety of robot-assisted surgery by implementing depth estimation using stereo images.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Ao Leng, Bolun Zeng, Yizhou Chen, Puxun Tu, Baoxin Tao, Xiaojun Chen
Summary: This study presents a novel training system for zygomatic implant surgery, which offers a more realistic simulation and training solution. By integrating visual, haptic, and auditory feedback, the system achieves global rigid-body collisions and soft tissue simulation, effectively improving surgeons' proficiency.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Yingjie Wang, Xueqing Yin
Summary: This study developed an integrated computational model combining coronary flow and myocardial perfusion models to achieve physiologically accurate simulations. The model has the potential for clinical application in diagnosing insufficient myocardial perfusion.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Nitzan Avidan, Moti Freiman
Summary: This study aims to enhance the generalization capabilities of DNN-based MRI reconstruction methods for undersampled k-space data. By introducing a mask-aware DNN architecture and training method, the under-sampled data and mask are encoded within the model structure, leading to improved performance. Rigorous testing on the widely accessible fastMRI dataset reveals that this approach demonstrates better generalization capabilities and robustness compared to traditional DNN methods.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Enhao Zhang, Saeed Miramini, Lihai Zhang
Summary: This study investigates the combined effects of osteoporosis and diabetes on fracture healing process by developing numerical models. The results show that osteoporotic fractures have higher instability and disruption in mesenchymal stem cells' proliferation and differentiation compared to non-osteoporotic fractures. Moreover, when osteoporosis coexists with diabetes, the healing process of fractures can be severely impaired.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Yunhao Bai, Wenqi Li, Jianpeng An, Lili Xia, Huazhen Chen, Gang Zhao, Zhongke Gao
Summary: This study proposes an effective MIL method for classifying WSI of esophageal cancer. The use of self-supervised learning for feature extractor pretraining enhances feature extraction from esophageal WSI, leading to more robust and accurate performance. The proposed framework outperforms existing methods, achieving an accuracy of 93.07% and AUC of 95.31% on a comprehensive dataset of esophageal slide images.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
