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Deep Learning-Enabled Clinically Applicable CT Planbox for Stroke With High Accuracy and Repeatability

Yang Wang, Junkai Zhu, Jinli Zhao, Wenyi Li, Xin Zhang, Xiaolin Meng, Taige Chen, Ming Li, Meiping Ye, Renfang Hu, Shidan Dou, Huayin Hao (+8 others)
2022 Frontiers in Neurology  
Real-time, accurate, and repeatable automatic scanning was accomplished with and a lower radiation exposure dose (all P < 0.001).ConclusionsCAPITAL-CT generated standard and reproducible images that  ...  Multiple cohorts including 1,124 patients were used for performance validation under three clinical scenarios.ResultsCranial Automatic Planbox Imaging Towards AmeLiorating neuroscience (CAPITAL)-CT was  ...  Chunfeng Qian who provided us with great help in image labeling.  ... 
doi:10.3389/fneur.2022.755492 pmid:35359626 pmcid:PMC8961979 fatcat:6mtuygke7ngp7arbf7yjahpzrq

Automated segmentation of the pulmonary arteries in low-dose CT by vessel tracking [article]

Jeremiah Wala, Sergei Fotin, Jaesung Lee, Artit Jirapatnakul, Alberto Biancardi, Anthony Reeves
2011 arXiv   pre-print
This fully-automated segmentation is a promising method for improving lung nodule detection in low-dose CT screening scans, by separating vessels from surrounding iso-intensity objects.  ...  We present a fully automated method for top-down segmentation of the pulmonary arterial tree in low-dose thoracic CT images.  ...  In low-dose CT lung cancer screening scans, there is the added challenge of a high signal-to-noise ratio compared with standard diagnostic CT scans.  ... 
arXiv:1106.5460v1 fatcat:lygywjnfczemjbpwod3u2k2gqm

Techniques for Lung Cancer Detection from CT Image

At present, there are huge number of tests available to detect lung cancer such as PET Scan, Computerized Tomography (CT) Scan and X-ray etc. are used to diagnose the disease.  ...  A further developed adaption found in CT scan which can uncover the small lesions in the lung that probably won't be distinguished with X-ray.  ...  When one repeats them spatially, they estimate the optimal sparse structure with thick components.  ... 
doi:10.35940/ijitee.b1105.1292s19 fatcat:hb35ch4sbrgupibpuwji2hsxze

Mathematical Methods and Applications in Medical Imaging 2014

Liang Li, Tianye Niu, Yi Gao
2015 Computational and Mathematical Methods in Medicine  
Few-view CT scanning is a promising low-dose CT imaging mode in applications. B.  ...  Zhang et al. present a method automatically detecting the hinge point of mitral annulus in echocardiography by combining local context feature with additive support vector machines classifier. R.  ...  Few-view CT scanning is a promising low-dose CT imaging mode in applications. assess the robustness and reliability of an adaptive thresholding algorithm for the Biological Target Volume estimation incorporating  ... 
doi:10.1155/2015/685036 pmid:26078778 pmcid:PMC4452828 fatcat:fsr34ggaabgfhptmnoevk4df6q

Automatic Segmentation and Quantification of White and Brown Adipose Tissues from PET/CT Scans

Sarfaraz Hussein, Aileen Green, Arjun Watane, David Reiter, Xinjian Chen, Georgios Z. Papadakis, Bradford Wood, Aaron Cypess, Medhat Osman, Ulas Bagci
2017 IEEE Transactions on Medical Imaging  
In this paper, we investigate the automatic detection of white and brown adipose tissues using Positron Emission Tomography/Computed Tomography (PET/CT) scans, and develop methods for the quantification  ...  In the first module, we detect white adipose tissue (WAT) and its two sub-types from CT scans: Visceral Adipose Tissue (VAT) and Subcutaneous Adipose Tissue (SAT).  ...  Specifically, we proposed a novel approach to automatically detect and quantify BAT from PET/CT scans involving PET guided CT co-segmentation, and a new probabilistic distance metric combining Total Variation  ... 
doi:10.1109/tmi.2016.2636188 pmid:28114010 fatcat:pibwd2ckhrfrjde5s3h756pqna

Artificial intelligence in image reconstruction: The change is here

Ramandeep Singh, Weiwen Wu, Ge Wang, Mannudeep K. Kalra
2020 Physica medica (Testo stampato)  
The range and speed of CT scanning improved from the introduction of multidetector-row CT scanners with wide-array detectors and faster gantry rotation speeds.  ...  Innovations in CT have been impressive among imaging and medical technologies in both the hardware and software domain.  ...  For children and patients who are unable to hold still during image acquisition, faster scanning can help reduce motion artifacts and the need for repeat scanning.  ... 
doi:10.1016/j.ejmp.2020.11.012 pmid:33246273 fatcat:bmozmptgg5frdhgbp6qmof75ty

Fast and robust adaptation of organs-at-risk delineations from planning scans to match daily anatomy in pre-treatment scans for online-adaptive radiotherapy of abdominal tumors

Vikas Gupta, Yibing Wang, Alejandra Méndez Romero, Andriy Myronenko, Petr Jordan, Calvin Maurer, Ben Heijmen, Mischa Hoogeman
2018 Radiotherapy and Oncology  
Results: For all OARs, DIR achieved average DSC, MHD and MSE of 86%, 2.1 mm, and 1.7 mm, respectively, within 20 s for each repeat CT.  ...  Materials and methods: For 20 liver cancer patients, planning OAR delineations were adapted to daily anatomy using the DIR on corresponding repeat CTs.  ...  Such fields, when applied to the planning delineations, resulted in automatically segmented or DIR-adapted OARs in the repeat CTs.  ... 
doi:10.1016/j.radonc.2018.02.014 pmid:29526492 fatcat:7jbkcdyp4nbvvjsfyldz5e3zfy

Improvements in Micro-CT Method for Characterizing X-ray Monocapillary Optics [article]

Zhao Wang, Kai Pan, Shuang Zhang, Zhuxuan Duo, Zhiguo Liu, Tianxi Sun
2021 arXiv   pre-print
In this paper, sparse sampling was proposed to shorten the scanning time, GPU acceleration technology was used to improve the speed of image reconstruction, and a simple geometric calibration algorithm  ...  These methodologies will popularize the use of the micro-CT method in XMCO characterization.  ...  In conclusion, sparse sampling can greatly reduce the time consumption of micro-CT scanning and effectively suppress the time-related errors caused by the power fluctuation and focus shift of the X-ray  ... 
arXiv:2106.15410v2 fatcat:yntnbserbzh2pmrd4zmtbzisae

Deep, dense and accurate 3D face correspondence for generating population specific deformable models

Syed Zulqarnain Gilani, Ajmal Mian, Peter Eastwood
2017 Pattern Recognition  
We evaluate our algorithm on the tasks of facial landmark detection and recognition using two benchmark datasets.  ...  We present a multilinear algorithm to automatically establish dense point-to-point correspondence over an arbitrarily large number of population specific 3D faces across identities, facial expressions  ...  The authors thank NVIDIA for providing the GeForce GTX TITAN X GPU used in our experiments.  ... 
doi:10.1016/j.patcog.2017.04.013 fatcat:yojkbm36wjccnnstz66wj27ifu

Robust segmentation using non-parametric snakes with multiple cues for applications in radiation oncology

Jayashree Kalpathy-Cramer, Umut Ozertem, William Hersh, Martin Fuss, Deniz Erdogmus, Josien P. W. Pluim, Benoit M. Dawant
2009 Medical Imaging 2009: Image Processing  
Radiation oncologists often manually delineate normal and diseased structures on 3D-CT scans, a time consuming task.  ...  The notion of principal curves is used to interpolate between data points in sparse areas.  ...  Apiradee Srisuthep, Research Fellow in the Department of Radiation Medicine, OHSU, Portland, OR for her help in acquiring the manually labeled data.  ... 
doi:10.1117/12.812712 dblp:conf/miip/Kalpathy-Cramer09 fatcat:tilkihcudfax3ey7uld7fd63sa

Auto-detection of motion artifacts on CT pulmonary angiograms with a physician-trained AI algorithm [article]

Giridhar Dasegowda, Bernardo C. Bizzo, Parisa Kaviani, Lina Karout, Shadi Ebrahimian, Subba R Digumarthy, Nir Neumark, James M Hillis, Mannudeep K Kalra, Keith J Dreyer
2022 medRxiv   pre-print
Purpose: Motion-impaired CT images can result in limited or suboptimal diagnostic interpretation (with missed or miscalled lesions) and patient recall.  ...  Clinical relevance : The AI model used in the study can help alert the technologists about the presence of substantial motion artifacts on CTPA where a repeat image acquisition can help salvage diagnostic  ...  The AI model's performance can however vary with the change in scan protocols (low dose chest CT versus CTPA protocols) and scanners (for those scanners without input training data).  ... 
doi:10.1101/2022.06.23.22276818 fatcat:lwkbwb5cpbbs5galvklqpckv4y

Efficient 3D Reconstruction for Urban Scenes [chapter]

Weichao Fu, Lin Zhang, Hongyu Li, Xinfeng Zhang, Di Wu
2013 Lecture Notes in Computer Science  
Finally, we recover the entire architectural models through an automatic growing algorithm of the sub-structures in dominant directions.  ...  Given a set of calibrated photographs, we first generate point clouds using an existing MVS algorithm, and then reconstruct the sub-structures that often regularly repeat in urban buildings.  ...  sparse outliers which will corrupt the estimation of local point cloud attributes such as surface normal or curvature changes.  ... 
doi:10.1007/978-3-642-39479-9_64 fatcat:qxivtrqri5bkra477nqtgtzszu

Do we need a new CT scan for retreatment of intracranial SRS patients?

David Wiant, Matthew Manning, Kyle Koch, Jacqueline Maurer, Lane Hayes, Han Liu, Qingyang Shang, Benjamin Sintay
2017 Journal of Applied Clinical Medical Physics  
Magnetic resonance scans from repeat SRS (rMR) courses were registered to CT scans from the initial SRS (iCT) and repeat SRS (rCT).  ...  The distance from each target to proximal skull surface was measured in 16 directions on each CT scan after registration.  ...  ACKNOWLEDGMENTS The authors would like to thank Peter Buccini for the help in gathering the data. CONF LICT OF I NTEREST The authors declare no conflict of interest. R E F E R E N C E S  ... 
doi:10.1002/acm2.12152 pmid:28771971 pmcid:PMC5875825 fatcat:qnoopegqgbaxtcflvg4wumkjoa

Towards automatic 3D bone marrow segmentation

Chuong T. Nguyen, Joseph P. Havlicek, Jennifer Holter Chakrabarty, Quyen Duong, Sara K. Vesely
2016 2016 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI)  
We propose an automatic framework for segmenting spinal marrow compartments to characterize the bone marrow from full-body joint PET/CT scans acquired subsequent to bone marrow transplantation.  ...  This fully automated approach achieves an average accuracy of 91.7% and a worst case accuracy of 80.4% in testing on 51 scans of 17 patients.  ...  In addition, the manual designation of consistent, identical ROIs in scans of a single patient acquired over time is nontrivial.  ... 
doi:10.1109/ssiai.2016.7459162 dblp:conf/ssiai/NguyenHCDV16 fatcat:cdier6bnabhwfbeod4kyuuvh7y

Ultrasound Painting of Liver Vascular Tree [article]

Asmund Birkeland, Ivan Viola
2010 International Symposium on Vision, Modeling, and Visualization  
Automatically detecting branching, this technique can handle complex structures, such as liver vessel trees, and track multiple regions simultaneously.  ...  In this paper we will present a novel approach to extract features from tracked 2D ultrasound, in particular hypo-echoic regions such as blood vessels.  ...  Acknowledgements This work has been carried out within the IllustraSound research project (# 193170), which is funded by the VERDIKT program of the Norwegian Research Council with support of the MedViz network in  ... 
doi:10.2312/pe/vmv/vmv10/163-170 dblp:conf/vmv/BirkelandV10 fatcat:e7rx7iijijfhdnlyrg3hndumeu
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