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Feature-Based Approach for Severity Scoring of Lung Tuberculosis from CT Images

Kirill Bogomasov, Ludmila Himmelspach, Gerhard Klassen, Martha Tatusch, Stefan Conrad
2018 Conference and Labs of the Evaluation Forum  
As part of ImageCLEF 2018, we investigated whether the severity of the disease can be determined from CT scans, only.  ...  We therefore extracted features from the images which we then tested with several classifiers. Afterwards we chose the best combinations of different feature sets and classification models.  ...  In this paper we present a feature-based approach for severity scoring of lung tuberculosis exclusively based on CT scans.  ... 
dblp:conf/clef/BogomasovHKT018 fatcat:ysad3x56mzfrzi7p5q6pqliuyu

Texture-based Graph Model of the Lungs for Drug Resistance Detection, Tuberculosis Type Classification, and Severity Scoring: Participation in ImageCLEF 2018 Tuberculosis Task

Yashin Dicente Cid, Henning Müller
2018 Conference and Labs of the Evaluation Forum  
In 2018, ImageCLEF proposed a task using CT (Computed Tomography) scans of patients with tuberculosis (TB).  ...  The task was divided into three subtasks: multi-drug resistance detection, TB type classification, and severity scoring.  ...  However, they base their final score on other clinical data as well as on the image. When tuberculosis affects the lungs, several visual patterns can be seen in a CT image.  ... 
dblp:conf/clef/CidM18 fatcat:zxq72ycbp5h5jkfkyje7lpxylq

Texture Analysis from 3D Model and Individual Slice Extraction for Tuberculosis MDR Detection, Type Classification and Severity Scoring

Md Sajib Ahmed, Sk Md Obaidullah, Mohan Jayatilake, Teresa Gonçalves, Luís Miguel Rato
2018 Conference and Labs of the Evaluation Forum  
Tuberculosis ImageCLEF 2018 proposes a set of tasks based on Computed Tomography (CT) scan images of patients' lungs.  ...  In accordance with the ranking given by the organizers, this approach was ranked 1 st for multi-drug resistance detection, 5 th for tuberculosis type classification and 3 rd tuberculosis severity scoring  ...  Acknowledgment The authors thank the LEADER and gLINK Erasmus Mundus projects for supporting this research.  ... 
dblp:conf/clef/AhmedSJGR18 fatcat:j3sb72wnafdb7kjowkp2rtj65y

ImageCLEF 2019: Projection-based CT Image Analysis for TB Severity Scoring and CT Report Generation

Vitali Liauchuk
2019 Conference and Labs of the Evaluation Forum  
Deep Learning methods were used to predict most of the features of CT images of patients with lung tuberculosis (TB). For part of the features, conventional methods were used.  ...  This paper presents an approach for automated analysis of 3D Computed Tomography (CT) images based on representing the 3D CT data as a set of 2D projection images along all three axes.  ...  Acknowledgements This study was partly supported by the National Institute of Allergy and Infectious Diseases, National Institutes of Health, U.S.  ... 
dblp:conf/clef/Liauchuk19 fatcat:2hu2ufnvm5d5xohqnl5grvmety

Revealing Lung Affections from CTs. A Comparative Analysis of Various Deep Learning Approaches for Dealing with Volumetric Data [article]

Radu Miron, Cosmin Moisii, Mihaela Breaban
2020 arXiv   pre-print
The paper presents and comparatively analyses several deep learning approaches to automatically detect tuberculosis related lesions in lung CTs, in the context of the ImageClef 2020 Tuberculosis task.  ...  Three classes of methods, different with respect to the way the volumetric data is given as input to neural network-based classifiers are discussed and evaluated.  ...  We would like to thank Mirela Iordache, an outstanding radiologist at the Regional Institute of Oncology in Iasi, for sharing her knowledge and valuable insights on the medical niche approached in the  ... 
arXiv:2009.04160v1 fatcat:cftyaxevzbc7zam7zviaxniz5e

A Survey of Deep Learning for Lung Disease Detection on Medical Images: State-of-the-Art, Taxonomy, Issues and Future Directions

Stefanus Tao Hwa Kieu, Abdullah Bade, Mohd Hanafi Ahmad Hijazi, Hoshang Kolivand
2020 Journal of Imaging  
Hence, numerous work on the detection of lung disease using deep learning can be found in the literature. This paper presents a survey of deep learning for lung disease detection in medical images.  ...  The recent developments of deep learning support the identification and classification of lung diseases in medical images.  ...  The goal is to estimate the tuberculosis severity based on the CT image.  ... 
doi:10.3390/jimaging6120131 pmid:34460528 fatcat:jhi5r4nj5nccbklrdbtuk4qo6e

ImageCLEF 2019: A 2D Convolutional Neural Network Approach for Severity Scoring of Lung Tuberculosis using CT Images

Kavitha S, Nandhinee P. R, Harshana S, Jahnavi Srividya S, Harrinei K
2019 Conference and Labs of the Evaluation Forum  
The achieved result is placed 9 th in the overall leaderboard of the ImageCLEF 2019 Tuberculosis challenge for severity scoring .  ...  We have taken up one sub-task that aims at assessing the severity of the tuberculosis disease as low or high.  ...  In this paper, a Convolutional Neural Network (CNN) approach for severity scoring of lung tuberculosis based on CT scans is discussed with results.  ... 
dblp:conf/clef/SRSSK19 fatcat:cba4x7zbnfb2hgixgmresuyz4q

A fully automatic artificial intelligence–based CT image analysis system for accurate detection, diagnosis, and quantitative severity evaluation of pulmonary tuberculosis

Chenggong Yan, Lingfeng Wang, Jie Lin, Jun Xu, Tianjing Zhang, Jin Qi, Xiangying Li, Wei Ni, Guangyao Wu, Jianbin Huang, Yikai Xu, Henry C. Woodruff (+1 others)
2021 European Radiology  
For training and validation of the model, 1921 lesions were manually labeled, classified according to six categories of critical imaging features, and visually scored regarding lesion involvement as the  ...  This study aims to develop an artificial intelligence (AI)-based fully automated CT image analysis system for detection, diagnosis, and burden quantification of pulmonary TB.  ...  The computerized quantitative approach provided segmentation of the lung tissues based on thresholds and adaptive region growing.  ... 
doi:10.1007/s00330-021-08365-z pmid:34842959 pmcid:PMC8628489 fatcat:htc6kl7fvnb5dfzue6rv3gdrmu

ImageCLEFmed Tuberculosis 2019: Predicting CT Scans Severity Scores using Stage-Wise Boosting in Low-Resource Environments

Augustus Tabarcea, Valentin Rosca, Adrian Iftene
2019 Conference and Labs of the Evaluation Forum  
required from the CT scan using a regularized variant of the SAMME.R algorithm.  ...  In the ImageCLEF 2019 Tuberculosis, our group submitted a solution that addresses the problem of tuberculosis' severity prediction in low-resource environments by attempting to minimize the information  ...  The first task involves automated detection of tuberculosis severity, while the second one involves a computed tomography report based on CT scans and the patient's metadata.  ... 
dblp:conf/clef/TabarceaRI19 fatcat:2gthdfmpu5gvhklnp6hkjqunpm

Overview of ImageCLEFtuberculosis 2018 - Detecting Multi-Drug Resistance, Classifying Tuberculosis Types and Assessing Severity Scores

Yashin Dicente Cid, Vitali Liauchuk, Vassili Kovalev, Henning Müller
2018 Conference and Labs of the Evaluation Forum  
In the case of the severity score task, the results support the suitability of assessing the severity based only on the CT image, as the results obtained were very good.  ...  severity score.  ...  of Health, U.S.  ... 
dblp:conf/clef/CidLKM18 fatcat:5niyn742vjcprk6zqafeteacsi

Identifying tuberculosis type in CTs

Cosmin Moisii, Radu Miron, Mihaela Breaban
2021 Conference and Labs of the Evaluation Forum  
The paper proposes and compares two distinct approaches based on deep learning for tuberculosis classification in CTs, highlighting the benefits of building the inference engine at slice-level over a volumetric  ...  approach.  ...  In case of frequency equality the prediction with the highest score is chosen. The second method is based on the mean of the scores for each label (MS 3DNLR50).  ... 
dblp:conf/clef/Moisii0B21 fatcat:vvadyecccrhelirm6skbxyeubi

Deep Learning based TB Severity Prediction

Ujjwel Balwal, Srinivasa Arun Yeragudipati, Bhuvana Jayaraman, Mirnalinee Thanga Nadar Thanga Thai
2020 Conference and Labs of the Evaluation Forum  
This paper presents an approach for predicting the presence of tuberculosis, caverns and pleurisy in a set of 3D CT scans of the chests of patients, which is the key task of the ImageCLEF 2020 Tuberculosis  ...  An AlexNet based model is used to predict the probability of the presence of tuberculosis, caverns and pleurisy from these 2D projections.  ...  This approach of analyzing 3D CT images of lungs for Tuberculosis consists of projecting the 3D image into 2D on the three planes -XY, YZ and XZ respectively.  ... 
dblp:conf/clef/BalwalYJT20 fatcat:l2hhdjqoufhp5f6u3ywwlmy6wq

Predicting Tuberculosis Related Lung Deformities from CT Scan Images Using 3D CNN

Anup Pattnaik, Sarthak Kanodia, Rahul Chowdhury, Smita Mohanty
2019 Conference and Labs of the Evaluation Forum  
CT scan of lung has become an invaluable tool in the diagnosis of tuberculosis. However, analysis of 3-D image data is time consuming and relies heavily on trained expertise.  ...  The approach comprises of detailed image processing, followed by feature extraction using tensor flow and 3-D CNN to further augment the metadata with the features extracted from the image data and finally  ...  The aim of the severity scoring subtask was to assess TB severity score on a scale of 1 (critical) to 5 (very good), whereas that of the CT report subtask was to generate an automatic report based on CT  ... 
dblp:conf/clef/PattnaikKCM19 fatcat:bfynuo4dxvhpfbfiuktgolu2ba

ImageCLEF 2019: CT Image Analysis for TB Severity Scoring and CT Report Generation using Autoencoded Image Features

Siarhei Kazlouski
2019 Conference and Labs of the Evaluation Forum  
This paper presents a possible approach for the automated analysis of 3D Computed Tomography (CT) images based on the usage of feature vectors extracted by a deep convolutional 3D autoencoder network.  ...  The proposed CT image analysis approach was used by participant UIIP (Siarhei Kazlouski) for accomplishing the two subtasks of the ImageCLEF Tuberculosis task of the ImageCLEF 2019 international competition  ...  Acknowledgements This study was partly supported by the National Institute of Allergy and Infectious Diseases, National Institutes of Health, U.S.  ... 
dblp:conf/clef/Kazlouski19 fatcat:zfqdjuxrvjdtjacypuffc3lhmi

Routine Pulmonary Function Test Can Estimate the Extent of Tuberculous Destroyed Lung

Eun Joo Lee, Sang Yeub Lee, Kwang Ho In, Se Hwa Yoo, Eun Jeong Choi, Yu Whan Oh, Sanghoon Park
2012 The Scientific World Journal  
To evaluate the degree of destruction, the Goddard classification scoring system was modified into a novel scoring system (destroyed lung score, (DLS)) with a score from 0 to 4.  ...  We investigated the feature of respiratory impairment of TDL patients, and studied whether extent of destroyed lung measured with chest CT has any correlation with routine lung function.  ...  In TDL, respiratory impairment originates from several anatomical features.  ... 
doi:10.1100/2012/835031 pmid:22666158 pmcid:PMC3361332 fatcat:bcutqkdkbjf5lptrlx4i7mg2g4
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