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Editorial: Bio-Inspired Physiological Signal(s) and Medical Image(s) Neural Processing Systems Based on Deep Learning and Mathematical Modeling for Implementing Bio-Engineering Applications in Medical and Industrial Fields

Francesco Rundo, Giuseppe Luigi Banna, Concetto Spampinato, Sabrina Conoci
2021 Frontiers in Neuroinformatics  
models and multimodal data analysis.  ...  The correlated target of the Research Topic was also to highlight the significant contribution of multimodal data analysis (signals and images) in the medical and industrial field.  ...  Another promising pipeline based on multimodal data analysis for applications in the medical field can be found in the contribution (Bartoletti et al.)  ... 
doi:10.3389/fninf.2021.763699 pmid:34776917 pmcid:PMC8586079 fatcat:ozk4ujfxkbgtphydb5ep64l2t4

Process analysis and application summary of surgical navigation system

Jincai Chang, Weina Wu, Zhao Su, Liyuan Ma, Jianzhong Cui
2020 Journal of Complexity in Health Sciences  
In recent years, with the rapid development of computer image processing technology, medical image technology and location tracking technology, computer-aided navigation system helps doctors to determine  ...  In this paper, the key technologies, process analysis, function realization and clinical application progress of surgical navigation system are briefly summarized.  ...  Current surgical navigation systems are mostly based on a medical image, mainly the physiological structure of CT/MRI/US.  ... 
doi:10.21595/chs.2020.21265 fatcat:sur2wrpz5jeblpuwujo476uyxq

Hierarchical microimaging for multiscale analysis of large vascular networks

Stefan Heinzer, Thomas Krucker, Marco Stampanoni, Rafael Abela, Eric P. Meyer, Alexandra Schuler, Philipp Schneider, Ralph Müller
2006 NeuroImage  
We developed a method based on modified vascular corrosion casting (VCC), scanning electron microscopy (SEM), and desktop and synchrotron radiation ACT (SRACT) technologies to image vasculature at increasing  ...  and vascular alterations in models of disease.  ...  Acknowledgments We would like to thank Adriane Mosley and Sarah Morgan (The Scripps Research Institute, San Diego, USA) for their help breeding the animals.  ... 
doi:10.1016/j.neuroimage.2006.03.043 pmid:16697665 fatcat:6jpdarx7fbapzdfcujlqzcwunm

3D Imaging and Quantitative Analysis of Vascular Networks: A Comparison of Ultramicroscopy and Micro-Computed Tomography

Jeremy Epah, Katalin Pálfi, Franziska Luise Dienst, Pedro Felipe Malacarne, Rolf Bremer, Michael Salamon, Sandeep Kumar, Hanjoong Jo, Christoph Schürmann, Ralf Peter Brandes
2018 Theranostics  
Rationale: Classic histology is the gold standard for vascular network imaging and analysis. The method however is laborious and prone to artefacts.  ...  Whereas UM is ideal for imaging and especially quantifying capillary networks and arterioles, larger vascular structures are easier and faster to quantify and visualize using micro-CT. 3D information of  ...  Acknowledgement We are grateful for the excellent technical assistance of Susanne Schütz and Mustapha Khabta. We thank Andrea Vasconez for critical reading of the manuscript.  ... 
doi:10.7150/thno.22610 pmid:29721067 pmcid:PMC5928875 fatcat:mxjppkmidjck3fomc6b7bvkkre

Computational medical imaging and hemodynamics framework for functional analysis and assessment of cardiovascular structures

Kelvin K. L. Wong, Defeng Wang, Jacky K. L. Ko, Jagannath Mazumdar, Thu-Thao Le, Dhanjoo Ghista
2017 BioMedical Engineering OnLine  
Diagnostic modalities based on echocardiography, magnetic resonance imaging, chest radiography and computed tomography are common techniques that provide cardiovascular structural information to diagnose  ...  and their surgical restoration, by means of an integrated medical image diagnostics and hemodynamic performance analysis framework.  ...  From medical imaging modalities such as the ultrasound, MRI or CT scans of cardiac chambers such as the left ventricle (LV) myocardium, the wall boundary can be extracted and reconstructed to derive the  ... 
doi:10.1186/s12938-017-0326-y pmid:28327144 pmcid:PMC5359907 fatcat:d4yd3q5eq5gozh5qrbc4d724qa

Epicardial and pericardial fat analysis on CT images and artificial intelligence: a literature review

Federico Greco, Rodrigo Salgado, Wim Van Hecke, Romualdo Del Buono, Paul M. Parizel, Carlo Augusto Mallio
2021 Quantitative Imaging in Medicine and Surgery  
Manual segmentation of medical images allows to obtain quantitative and qualitative data on several tissues including epicardial and pericardial fat.  ...  Body composition imaging is a novel concept based on quantitative analysis of body tissues.  ...  These two models are fully connected neural network and CNNs respectively, being the latter learning model the most used technique in medical imaging analyses.  ... 
doi:10.21037/qims-21-945 pmid:35284252 pmcid:PMC8899943 fatcat:emmvldqdmzeezh43m2ocumbepi

Micro-morphological feature visualization, auto-classification, and evolution quantitative analysis of tumors by using SR-PCT

Gong-Xiang Wei, Yun-Yan Liu, Xue-Wen Ji, Qiao-Xin Li, Yan Xing, Yan-Ling Xue, Hui-Qiang Liu
2021 Cancer Medicine  
However, the multiscale three-dimensional nondestructive pathological visualization, measurement, and quantitative analysis are still a challenging for the medical imaging and diagnosis.  ...  Hence, this high phase-contrast 3D pathological characteristics and automatic analysis methods exhibited excellent recognizable and classifiable for micro tumor lesions.  ...  ACKNOWLEDGMENTS We thank the staffs from the BL13W beamline at Shanghai Synchrotron Radiation Facility (SSRF) for assistance during data collection.  ... 
doi:10.1002/cam4.3796 pmid:33682368 fatcat:3btx6meb4bapna4axhq3djmzwe

Automated analysis of whole brain vasculature using machine learning [article]

Mihail Ivilinov Todorov, Johannes C. Paetzold, Oliver Schoppe, Giles Tetteh, Velizar Efremov, Katalin Voelgyi, Marco Duering, Martin Dichgans, Marie Piraud, Bjoern Menze, Ali Erturk
2019 bioRxiv   pre-print
Tissue clearing methods enable imaging of intact biological specimens without sectioning. However, reliable and scalable analysis of such large imaging data in 3D remains a challenge.  ...  Towards this goal, we developed a deep learning-based framework to quantify and analyze the brain vasculature, named Vessel Segmentation & Analysis Pipeline (VesSAP).  ...  Step 2: Segmentation of the volumetric images To enable extraction of quantitative features of the vascular structure, the vessels in the acquired brain scans need to be segmented in 3D.  ... 
doi:10.1101/613257 fatcat:233qaac4mbf53h42x2vlrbs74u

Personalizing Medicine Through Hybrid Imaging and Medical Big Data Analysis

Laszlo Papp, Clemens P. Spielvogel, Ivo Rausch, Marcus Hacker, Thomas Beyer
2018 Frontiers in Physics  
This paper provides a general insight into medical big data analysis in light of the use of hybrid imaging information.  ...  These challenges increase in complexity when employing hybrid, aka dual-or even multi-modality image data as input to big data repositories.  ...  Hadoop has been applied to address numerous tasks in medical imaging, such as parameter optimization for lung texture segmentation, content-based medical image indexing, and 3D directional wavelet analysis  ... 
doi:10.3389/fphy.2018.00051 fatcat:3ikjf4gqwfao5dngsqepuhmetu

Shape Analysis in Molecular Imaging [chapter]

Fei Gao, Pengcheng Shi
2014 Lecture Notes in Computational Vision and Biomechanics  
inaccuracy of blood samplings from patients, the low Signal-to-Noise (SNR) ratio of measurement data in dynamic PET/CT scan.  ...  However, some limitations from molecular imaging modalities and clinical practices still hinder the quantitative accuracy of shape analysis, e.g. the low spatial and temporal resolution in PET scan, the  ...  Based on these imaging modalities, hybrid PET/CT [90] , PET/MRI [74] , PET/SPECT/CT [56] further enrich the ability of molecular imaging.  ... 
doi:10.1007/978-3-319-03813-1_2 fatcat:ys6aqt32lnadnikrog7ywjhs5y

Medical image analysis: progress over two decades and the challenges ahead

J.S. Duncan, N. Ayache
2000 IEEE Transactions on Pattern Analysis and Machine Intelligence  
AbstractÐThe analysis of medical images has been woven into the fabric of the Pattern Analysis and Machine Intelligence (PAMI) community since the earliest days of these Transactions.  ...  In this paper, we look at progress in the field over the last 20 years and suggest some of the challenges that remain for the years to come.  ...  ACKNOWLEDGMENTS The authors would like to thank Eric Grimson, Anond Rangarajan, Larry Staib, Hemant Tagare, and the Epidaure team at INRIA for their helpful discussions.  ... 
doi:10.1109/34.824822 fatcat:csqincxgozelphrz62ncrexqo4

Myocardial perfusion analysis in cardiac computed tomography angiographic images at rest

Guanglei Xiong, Deeksha Kola, Ran Heo, Kimberly Elmore, Iksung Cho, James K. Min
2015 Medical Image Analysis  
After initialization with five anatomical landmarks, the model is adapted to a target image by  ...  Both endocardium and epicardium are compactly modeled with subdivision surfaces and coupled by explicit thickness representation.  ...  Acknowledgments This work was supported by the National Institutes of Health via grants R01HL115150 and R01HL118019. We are also grateful for the comments and suggestions from the reviewers.  ... 
doi:10.1016/ pmid:26073787 pmcid:PMC4536577 fatcat:bgftdmkuufez5iysd4gutkntte

Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Future

David Ahmedt-Aristizabal, Mohammad Ali Armin, Simon Denman, Clinton Fookes, Lars Petersson
2021 Sensors  
We provide an overview of these methods in a systematic manner, organized by their domain of application including functional connectivity, anatomical structure, and electrical-based analysis.  ...  A major limitation of existing methods has been the focus on grid-like data; however, the structure of physiological recordings are often irregular and unordered, which makes it difficult to conceptualise  ...  Acknowledgments: Not applicable. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/s21144758 fatcat:jytyt4u2pjgvhnhcto3vcvd3a4

AI-Based Detection, Classification and Prediction/Prognosis in Medical Imaging: Towards Radiophenomics [article]

Fereshteh Yousefirizi, Pierre Decazes, Amine Amyar, Su Ruan, Babak Saboury, Arman Rahmim
2022 arXiv   pre-print
This work reviews AI-based techniques, with a special focus on oncological PET and PET/CT imaging, for different detection, classification, and prediction/prognosis tasks.  ...  AI-based detection searches the image space to find the regions of interest based on patterns and features.  ...  Acknowledgements This project was in part supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant RGPIN-2019-06467, and the Canadian Institutes of Health Research  ... 
arXiv:2110.10332v4 fatcat:vmpxhoolarbrve5ddyfn5umfim

3D analysis of microvasculature in murine liver fibrosis models using synchrotron radiation-based microtomography

Willi L. Wagner, Sonja Föhst, Jessica Hock, Yong Ook Kim, Yury Popov, Detlef Schuppan, Katja Schladitz, Claudia Redenbach, Maximilian Ackermann
2020 Angiogenesis  
Here, we report on the application of high-resolution 3D synchrotron radiation-based microtomography (SRμCT) for the study of the sinusoidal and capillary blood vessel system in three murine models of  ...  To date, macrovascular remodeling in various cirrhosis models has been examined using three-dimensional (3D) imaging modalities, while microvascular changes have been studied mainly by two-dimensional  ...  Supported by Grants (HL94567 and HL134229, to MA) from the National Institutes of Health. We thank Dr. Pablo Villanueva and the staff of TOMCAT beamline for excellent assistance.  ... 
doi:10.1007/s10456-020-09751-9 pmid:33037487 fatcat:p4drn5ijofgrfnnynwprzueo2q
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