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Comparing algorithms for automated vessel segmentation in computed tomography scans of the lung: the VESSEL12 study

Rina D. Rudyanto, Sjoerd Kerkstra, Eva M. van Rikxoort, Catalin Fetita, Pierre-Yves Brillet, Christophe Lefevre, Wenzhe Xue, Xiangjun Zhu, Jianming Liang, İlkay Öksüz, Devrim Ünay, Kamuran Kadipaşaogˇlu (+36 others)
2014 Medical Image Analysis  
analysis of the strengths and weaknesses of the various vessel segmentation methods in the presence of various lung diseases.  ...  Our three contributions are: (1) an annotated reference dataset available online for evaluation of new algorithms; (2) a quantitative scoring system for objective comparison of algorithms; and (3) performance  ...  a b s t r a c t The VESSEL12 (VESsel SEgmentation in the Lung) challenge objectively compares the performance of different algorithms to identify vessels in thoracic computed tomography (CT) scans.  ... 
doi:10.1016/ pmid:25113321 pmcid:PMC5153359 fatcat:w5frt2g2rjgepjthnnciba444a

Extracting Lungs from CT Images using Fully Convolutional Networks [article]

Jeovane Honório Alves and Pedro Martins Moreira Neto and Lucas Ferrari de Oliveira
2018 arXiv   pre-print
Analysis of cancer and other pathological diseases, like the interstitial lung diseases (ILDs), is usually possible through Computed Tomography (CT) scans.  ...  Dice scores of 98.67%±0.94% for the HUG-ILD dataset and 99.19%±0.37% for the VESSEL12 dataset were achieved, outperforming works in the former and obtaining similar state-of-the-art results in the latter  ...  We would like to thank NVIDIA Corporation with the donation of the Titan Xp GPU used in our experiments.  ... 
arXiv:1804.10704v1 fatcat:tvsg3yqffzhmldqcj6v65h3pxm

Lung Vessel Enhancement in Low-Dose CT Scans [chapter]

Nico Merten, Kai Lawonn, Philipp Gensecke, Oliver Großer, Bernhard Preim
2018 Bildverarbeitung für die Medizin 2018  
To reduce the patient's radiation exposure from computed tomography scans (CT), low-dose CT scans can be recorded.  ...  Several image processing methods exist to segment or enhance the lung blood vessels from contrast-enhanced or high resolution CT scans, but the reduced contrast in low-dose CT scans leads to over-or under-segmentation  ...  Acknowledgments: This work is partly funded by the Federal Ministry of Education and Research within the Forschungscampus STIMULATE (13GW0095A).  ... 
doi:10.1007/978-3-662-56537-7_88 dblp:conf/bildmed/MertenLGGP18 fatcat:67u4lkhduna53m4wpjsyjmgqca

Automatic lung segmentation in routine imaging is primarily a data diversity problem, not a methodology problem

Johannes Hofmanninger, Forian Prayer, Jeanny Pan, Sebastian Röhrich, Helmut Prosch, Georg Langs
2020 European Radiology Experimental  
For lung segmentation in computed tomography, a variety of approaches exists, involving sophisticated pipelines trained and validated on different datasets.  ...  Automated segmentation of anatomical structures is a crucial step in image analysis.  ...  Acknowledgements We would like to thank Mary McAllister for thorough proofreading of the article. Authors' contributions JH and GL developed the presented idea and designed the experiments.  ... 
doi:10.1186/s41747-020-00173-2 pmid:32814998 fatcat:emif34mnp5bgzpkc7x7tzjl6la

Lung Segmentation and Characterization in COVID-19 Patients for Assessing Pulmonary Thromboembolism: An Approach Based on Deep Learning and Radiomics

Vitoantonio Bevilacqua, Nicola Altini, Berardino Prencipe, Antonio Brunetti, Laura Villani, Antonello Sacco, Chiara Morelli, Michele Ciaccia, Arnaldo Scardapane
2021 Electronics  
The COVID-19 pandemic is inevitably changing the world in a dramatic way, and the role of computed tomography (CT) scans can be pivotal for the prognosis of COVID-19 patients.  ...  For eight CT scans, we obtained masks of the lesions caused by the infection, annotated by expert radiologists; whereas for the other four CT scans, we obtained masks of the lungs (including both healthy  ...  Therefore, we proposed an automated workflow for segmenting lung lesions and parenchyma, aiding the work of radiologists and posing the basis for further analysis on the segmented region.  ... 
doi:10.3390/electronics10202475 fatcat:uz4lx4jiezhxtgncmn5c662zea

Self-Supervised Vessel Enhancement Using Flow-Based Consistencies [article]

Rohit Jena, Sumedha Singla, Kayhan Batmanghelich
2021 arXiv   pre-print
Vessel segmentation is an essential task in many clinical applications.  ...  Unlike generic self-supervised methods, the learned features learn vessel-relevant features that are transferable for supervised approaches, which is essential when the number of annotated data is limited  ...  .: Comparing algorithms for automated vessel segmentation in computed tomogra- phy scans of the lung: the vessel12 study.  ... 
arXiv:2101.05145v3 fatcat:rq6npfva5jh3vcwxbx4emoa2lq

An Approach for Pulmonary Vascular Extraction from Chest CT Images

Wenjun Tan, Yue Yuan, Anning Chen, Lin Mao, Yuqian Ke, Xinhui Lv
2019 Journal of Healthcare Engineering  
To improve the accuracy rate of pulmonary vascular segmentation, a new pulmonary vascular extraction approach is proposed in this study.  ...  Pulmonary vascular extraction from chest CT images plays an important role in the diagnosis of lung disease.  ...  Introduction At present, computed tomography (CT) has become the most common imaging modality for the diagnosis of lung disease.  ... 
doi:10.1155/2019/9712970 pmid:30800258 pmcid:PMC6360062 fatcat:v7dlrn7wnzd5fatj35y5hyteea

AVATREE: An open-source computational modelling framework modelling Anatomically Valid Airway TREE conformations

Stavros Nousias, Evangelia I. Zacharaki, Konstantinos Moustakas, Fang-Bao Tian
2020 PLoS ONE  
Such conformations are obtained from the personalized 3D geometry generated from computed tomography (CT) data through image segmentation.  ...  It can be exploited in studies of gas flow, gas mixing, ventilation patterns and particle deposition in the pulmonary system, with the aim to improve clinical decision making.  ...  A literature review on the analysis of lung CTs, including segmentation of the various pulmonary structures, can be found in [16] , while a comparative study of automated and semi-automated segmentation  ... 
doi:10.1371/journal.pone.0230259 pmid:32243444 fatcat:y7kst7kfjnf63hh4b5jsgegu34

Deep Learning Convolutional Networks for Multiphoton Microscopy Vasculature Segmentation [article]

Petteri Teikari, Marc Santos, Charissa Poon, Kullervo Hynynen
2016 arXiv   pre-print
We derived the architectures from Lee et al. who used the ZNN framework initially designed for electron microscope image segmentation.  ...  We demonstrated the use of deep learning framework consisting both 2D and 3D convolutional filters (ConvNet). Our hybrid 2D-3D architecture produced promising segmentation result.  ...  Acknowledgements We would like to thank Sharan Sankar for his work as a summer student writing wrapper for various wrappers for ITK C++ functions.  ... 
arXiv:1606.02382v1 fatcat:v5jwomv4gbf7bhxe6yn2tbkhiq

A Systematic Collection of Medical Image Datasets for Deep Learning [article]

Johann Li, Guangming Zhu, Cong Hua, Mingtao Feng, BasheerBennamoun, Ping Li, Xiaoyuan Lu, Juan Song, Peiyi Shen, Xu Xu, Lin Mei, Liang Zhang (+2 others)
2021 arXiv   pre-print
The lack of data in the medical imaging field creates a bottleneck for the application of deep learning to medical image analysis.  ...  Deep learning algorithms are data-dependent and require large datasets for training.  ...  Acknowledgments We thanks for the projects of National Natural Science Foundation of China (62072358), Zhejiang University special scientific research fund for COVID-19 preverntion and control, National  ... 
arXiv:2106.12864v1 fatcat:bjzkgce2xvaexmb6cdznws7fye

Power pulsing of the CALICE tile hadron calorimeter

Mathias Reinecke
2016 2016 IEEE Nuclear Science Symposium, Medical Imaging Conference and Room-Temperature Semiconductor Detector Workshop (NSS/MIC/RTSD)  
This achievement was recognised through the award of the 2015 Nobel prize for physics to the leaders of the SNO and Super-Kamiokande experiments for the conclusive establishment of the phenomenon of neutrino  ...  Much of what we know about neutrinos comes from studying neutrino flavour oscillations, whereby one type of neutrino transforms into a different type as it propagates over a large distance.  ...  The principles will be described along with several examples of spectral X-ray radiography. R13-3: 3D Non-Destructive Fluorescent X-Ray Computed Tomography (FXCT) with a CdTe Array  ... 
doi:10.1109/nssmic.2016.8069748 fatcat:zjgd7dmfdbhntb4kfwdtrlejhi

Lung image segmentation and vision-based navigation for interventional bronchoscopy

Mali Shen, Guang-Zhong Yang, Pallav Shah, Imperial College London
Abnormalities identified on chest X-ray computed tomography (CT) scans by using computer-aided diagnosis are often targetted in bronchoscopic intervention.  ...  A validation study on a cohort of emphysema patients shows the reliability of the program by comparing with commercial software.  ...  The VESSEL12 (VESsel SEgmentation in the Lung) challenge compared multiple vessel segmentation approaches based on vascular models, image features and extraction schemes [74] .  ... 
doi:10.25560/83323 fatcat:jv5aqus5wva6tnxsipkyql6ura

Deep Learning Segmentation Algorithms for X-ray CT data

Tomasz Kazimierz Konopczynski
The techniques are evaluated on a dataset of CT scans of short glass fiber reinforced polymers prepared in cooperation with the University of Padova and on publicly available medical CT scans of lungs  ...  The reference setup consist of metrics for instance and semantic segmentation tasks as well as of a baseline, Frangi vesselness method.  ...  Comparing different algorithms for segmenting glass fibers in industrial computed tomography (CT) scans is difficult due to the absence of a standard reference dataset.  ... 
doi:10.11588/heidok.00030239 fatcat:6ccjso2dr5fsliocweaanxfgie

Joint registration and segmentation of CP-BOLD MRI

Ilkay Orsuz
In this thesis, novel techniques for the tasks of segmentation and registration are discussed separately and jointly.  ...  Joint registration and segmentation of varying contrast images is a fundamental task in the field of image analysis, despite yet open.  ...  ,Ortiz-de-Solorzano, C., Muñoz-Barrutia, A., van Ginneken, B., "Comparing algorithms for automated vessel segmentation in computed tomography scans of the lung: the VESSEL12 study", Medical Image Analysis  ... 
doi:10.6092/imtlucca/e-theses/238 fatcat:avneyq2h65gxzgsy47hizxjnmu