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Automated Nomenclature of Bronchial Branches Extracted from CT Images and Its Application to Biopsy Path Planning in Virtual Bronchoscopy [chapter]

Kensaku Mori, Sinya Ema, Takayuki Kitasaka, Yoshito Mekada, Ichiro Ide, Hiroshi Murase, Yasuhito Suenaga, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori
2005 Lecture Notes in Computer Science  
We propose a novel anatomical labeling algorithm for bronchial branches extracted from CT images. This method utilizes multiple branching models for anatomical labeling.  ...  As an application of the automated nomenclature of bronchial branches, we utilized anatomical labeling results for assisting biopsy planning.  ...  There are only a few reports on automated anatomical labeling of bronchial branches extracted from CT images [1, 2, 3] . Mori et al.  ... 
doi:10.1007/11566489_105 fatcat:c6sfokbsbzhxhjiruspkvy4m3y

Automated Nomenclature Labeling of the Bronchial Tree in 3D-CT Lung Images [chapter]

Hiroko Kitaoka, Yongsup Park, Juerg Tschirren, Joseph Reinhardt, Milan Sonka, Goeffrey McLennan, Eric A. Hoffman
2002 Lecture Notes in Computer Science  
A nomenclature labeling algorithm for the human bronchial tree down to sub-lobar segments is proposed, as a means of inter and intra subject comparisons for the evaluation of lung structure and function  ...  Experiments have been performed for nine airway trees extracted automatically from clinical 3D-CT data, where approximately 250 branches were contained. Of these, 95 % were accurately named.  ...  Mori et al reported a knowledge-based labeling method of the bronchial branches and applied it to seven cases of CT images with a slice thickness of 2 or 3 mm [1] .  ... 
doi:10.1007/3-540-45787-9_1 fatcat:if2n4kqqyfe7xhr4cvcepku4ry

Automatic segmentation and recognition of anatomical lung structures from high-resolution chest CT images

Xiangrong Zhou, Tatsuro Hayashi, Takeshi Hara, Hiroshi Fujita, Ryujiro Yokoyama, Takuji Kiryu, Hiroaki Hoshi
2006 Computerized Medical Imaging and Graphics  
A sequential region-splitting process is used to segment lungs, airway of bronchus, lung lobes and fissures based on the anatomical structures and statistical intensity distributions in CT images.  ...  The performance of our scheme is evaluated by segmenting lung structures from high-resolution multi-slice chest CT images from 44 patients; the validity of our method was proved by preliminary experimental  ...  Acknowledgements The authors thank the members of Fujita's Laboratory and the Virtual System Laboratory (VSL) of Gifu University for their collaboration.  ... 
doi:10.1016/j.compmedimag.2006.06.002 pmid:16920331 fatcat:tz3mv7qv5zccnkocchdzab75di

Robust Segmentation and Anatomical Labeling of the Airway Tree from Thoracic CT Scans [chapter]

Bram van Ginneken, Wouter Baggerman, Eva M. van Rikxoort
2008 Lecture Notes in Computer Science  
A method for automatic extraction and labeling of the airway tree from thoracic CT scans is presented and extensively evaluated on 150 scans of clinical dose, low dose and ultra-low dose data, in inspiration  ...  From inspiration scans on average 170 branches are found, from expiration scans 59.  ...  Introduction Multi-slice CT scanning technology has revolutionized the in vivo study of the lungs and motivates the need for pulmonary image analysis [1] .  ... 
doi:10.1007/978-3-540-85988-8_27 fatcat:u677etsrybdt3iylovmyhqn2h4

Automated anatomical description of pleural thickening towards improvement of its computer-assisted diagnosis

Kraisorn Chaisaowong, Mingze Jiang, Peter Faltin, Dorit Merhof, Christian Eisenhawer, Monika Gube, Thomas Kraus, Georgia D. Tourassi, Samuel G. Armato
2016 Medical Imaging 2016: Computer-Aided Diagnosis  
Finally, each detected pleural thickening is assigned a set of labels describing its anatomical properties.  ...  Today, pleural thickenings are detected by visual inspection of CT data, which is time-consuming and underlies the physician's subjective judgment.  ...  The performance of the anatomical labeling is evaluated based on three CT data sets consisting of 284 detected thickenings.  ... 
doi:10.1117/12.2216939 dblp:conf/micad/ChaisaowongJFME16 fatcat:maw7gby5rrhr3nggyow4idymqq

Bronchopulmonary segments approximation using anatomical atlas

Sata Busayarat, Tatjana Zrimec, Josien P. W. Pluim, Joseph M. Reinhardt
2007 Medical Imaging 2007: Image Processing  
A new ray-tracing based image registration is developed for transferring the information from the atlas to a query image.  ...  Traditionally, determining the segments requires segmentation and identification of segmental bronchi, which, in turn, require volumetric imaging data.  ...  Similar to how radiologists map an image to a pictorial atlas, our registration is based on anatomical landmarks and interpolation. Lung root is used to initially align a query scan to the atlas.  ... 
doi:10.1117/12.709651 dblp:conf/miip/BusayaratZ07 fatcat:rkmqrzdg4vhing6cbzfzpe2sg4

Computer-aided Analysis and Interpretation of HRCT Images of the Lung [chapter]

Zrimec Tatjana, Sata Busayarat
2011 Theory and Applications of CT Imaging and Analysis  
Applications of CT Imaging and Analysis  ...  We also thank radiologists Peter Wilson, Michael Jones Daniel Moses and Pravati Panigrahi for providing clinical resources, image annotation and inspection of the results. Theory and  ...  Consequently, most of the automated detection algorithms, being developed to analyse CT scans are texture based.  ... 
doi:10.5772/14507 fatcat:6zdivmedlzc4xdxgcs7ffalvpu

Extraction of Airways From CT (EXACT'09)

Pechin Lo, Bram van Ginneken, Joseph M. Reinhardt, Tarunashree Yavarna, Pim A. de Jong, Benjamin Irving, Catalin Fetita, Margarete Ortner, Rômulo Pinho, Jan Sijbers, Marco Feuerstein, Anna Fabijanska (+18 others)
2012 IEEE Transactions on Medical Imaging  
National Institutes of Health.  ...  Several automated methods have been proposed to segment the airway tree from CT images. Evaluation of these methods has been problematic.  ...  Figure 9b presents a diagram showing the sensitivity of the algorithms to the different anatomical labeled branches, which is def ned as the number of algorithms that detected (part of) a branch by the  ... 
doi:10.1109/tmi.2012.2209674 pmid:22855226 fatcat:6unhf2zlanc7joi335622svnoa

From lung images to lung models: A review

S. L. A. Lee, A. Z. Kouzani, E. J. Hu
2008 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)  
Automated 3D lung modeling involves analyzing 2D lung images and reconstructing a realistic 3D model of the lung.  ...  This paper presents a review of the existing works on automatic formation of 3D lung models from 2D lung images. A common framework for 3D lung modeling is proposed.  ...  ACKNOWLEDGMENT The support of the Victorian Partnership for Advanced Computing (VPAC) lUlder an e-Research Program Grants Scheme is gratefully acknowledged  ... 
doi:10.1109/ijcnn.2008.4634128 dblp:conf/ijcnn/LeeKH08 fatcat:74rnkdvoo5cxhmopimvz7kdwtu

Computer analysis of computed tomography scans of the lung: a survey

I. Sluimer, A. Schilham, M. Prokop, B. van Ginneken
2006 IEEE Transactions on Medical Imaging  
Automating the analysis of such data is, therefore, a necessity and this has created a rapidly developing research area in medical imaging.  ...  This paper presents a review of the literature on computer analysis of the lungs in CT scans and addresses segmentation of various pulmonary structures, registration of chest scans, and applications aimed  ...  Based upon such segmentations, computerized schemes have been developed to label the different bronchi such that branches with problems can be pinpointed anatomically [22] , [34] , [35] .  ... 
doi:10.1109/tmi.2005.862753 pmid:16608056 fatcat:q5ysngkgozbbrfwn7tbb2fvunu

Segmentation of the Airway Tree from Chest CT using Tiny Atrous Convolutional Network

Guohua Cheng, Xiaoming Wu, Wending Xiang, Chuan Guo, Hongli Ji, Linyang He
2021 IEEE Access  
In order to take into account the multi-scale changes of the airway and achieve accurate airway segmentation, we design an end-to-end Tiny Atrous Convolutional Network (TACNet) based on 3D convolution  ...  INDEX TERMS Airway classification, convolutional neural network, deep learning, semantic segmentation, CT, medical image.  ...  [9] used two passes of 3D seeded region growing to address problem of pulmonary airways investigation based on high-resolution multi-slice spiral CT chest scan. Zijian B et al.  ... 
doi:10.1109/access.2021.3059680 fatcat:g55kciuonjfu3is75zyv4546oq

Optimizing parameters of an open-source airway segmentation algorithm using different CT images

Pietro Nardelli, Kashif A Khan, Alberto Corvò, Niamh Moore, Mary J Murphy, Maria Twomey, Owen J O'Connor, Marcus P Kennedy, Raúl San José Estépar, Michael M Maher, Pádraig Cantillon-Murphy
2015 BioMedical Engineering OnLine  
In some conditions, having an airway segmentation method which facilitates reconstruction of the airway from chest CT images can help hugely in the assessment of lung diseases.  ...  The method is based on a region growing approach where trachea, right and left bronchi are cropped and segmented independently using three different thresholds.  ...  In this work, we describe a semi-automated algorithm for airway segmentation in CT images based on lung-side-specific region growing approach using the intensity range of pixels.  ... 
doi:10.1186/s12938-015-0060-2 pmid:26112975 pmcid:PMC4482101 fatcat:j5pme5pza5htbjzhpmifzu2eyq

Automatic Segmentation of the Pulmonary Lobes From Chest CT Scans Based on Fissures, Vessels, and Bronchi

Bianca Lassen, Eva M. van Rikxoort, Michael Schmidt, Sjoerd Kerkstra, Bram van Ginneken, Jan-Martin Kuhnigk
2013 IEEE Transactions on Medical Imaging  
In initial stage, the lobar markers are determined by the calculation of labeled bronchial tree. In initial stage of the work the pulmonary vessels are detected based on MMTD.  ...  The bronchial tree is mainly applied to enhance the quality of the input image samples.  ...  The image resolution of each plane is measured based on the 0.4mm, 0.8 mm, and the slice width among 0.5mm -1.5 mm.  ... 
doi:10.1109/tmi.2012.2219881 pmid:23014712 fatcat:uxuwrykshjagxhkf2b7c6rtjl4

Automatic Detection and Staging of Lung Tumors using Locational Features and Double-Staged Classifications

May Phu Paing, Kazuhiko Hamamoto, Supan Tungjitkusolmun, Chuchart Pintavirooj
2019 Applied Sciences  
This paper presents a computer-aided diagnosis (CAD) method for detecting and staging lung cancer from computed tomography (CT) images.  ...  Clinical staging of lung cancer can significantly reduce the mortality rate, because effective treatment options strongly depend on the specific stage of cancer.  ...  We would also like to thank The Cancer Imaging Archive (TCIA) for publically sharing the CT scan images and clinical data which were applied in our experiments.  ... 
doi:10.3390/app9112329 fatcat:dw32frowfvcmvk6vmp45nnhk6q

Segmentation of distal airways using structural analysis

Debora Gil, Carles Sanchez, Agnes Borras, Marta Diez-Ferrer, Antoni Rosell, Niels Bergsland
2019 PLoS ONE  
We have compared our method to the top performers of the EXACT09 challenge and to a commercial software for biopsy planning evaluated in an own-collected data-base of high resolution CT scans acquired  ...  We present a method that combines descriptors of bronchi local appearance and graph global structural analysis to fine-tune thresholds on the descriptors adapted for each bronchial level.  ...  The matching criterion uses a measure of anatomical consistency based on the complexity of a graph representation of the segmented airways.  ... 
doi:10.1371/journal.pone.0226006 pmid:31856216 pmcid:PMC6922352 fatcat:u2k22pv6hzfyngxxtni65ay3fe
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