21.7.3.9 Tuberculosis Analysis, Tuberculosis Bacilli

Chapter Contents (Back)
Chest X-Ray. Medical, Applications. Tuberculosis.

Forero, M.G.[Manuel G.], Sroubek, F.[Filip], Cristóbal, G.[Gabriel],
Identification of tuberculosis bacteria based on shape and color,
RealTimeImg(10), No. 4, August 2004, pp. 251-262.
Elsevier DOI 0410
BibRef

Xu, T.[Tao], Cheng, I.[Irene], Long, R.[Richard], Mandal, M.[Mrinal],
Novel coarse-to-fine dual scale technique for tuberculosis cavity detection in chest radiographs,
JIVP(2012), No. 1, 2013, pp. 3.
DOI Link 1302
BibRef

Jaeger, S., Karargyris, A., Candemir, S., Folio, L., Siegelman, J., Callaghan, F., Xue, Z.Y.[Zhi-Yun], Palaniappan, K., Singh, R.K., Antani, S., Thoma, G., Wang, Y.X.[Yi-Xiang], Lu, P.X.[Pu-Xuan], McDonald, C.J.,
Automatic Tuberculosis Screening Using Chest Radiographs,
MedImg(33), No. 2, February 2014, pp. 233-245.
IEEE DOI 1403
diagnostic radiography BibRef

Ayas, S.[Selen], Ekinci, M.[Murat],
Random forest-based tuberculosis bacteria classification in images of ZN-stained sputum smear samples,
SIViP(8), No. S1, December 2014, pp. 49-61.
WWW Link. 1411
BibRef

Melendez, J., van Ginneken, B., Maduskar, P., Philipsen, R.H.H.M., Reither, K., Breuninger, M., Adetifa, I.M.O., Maane, R., Ayles, H., Sanchez, C.I.,
A Novel Multiple-Instance Learning-Based Approach to Computer-Aided Detection of Tuberculosis on Chest X-Rays,
MedImg(34), No. 1, January 2015, pp. 179-192.
IEEE DOI 1502
diagnostic radiography BibRef

Melendez, J., van Ginneken, B., Maduskar, P., Philipsen, R.H.H.M., Ayles, H., Sánchez, C.I.,
On Combining Multiple-Instance Learning and Active Learning for Computer-Aided Detection of Tuberculosis,
MedImg(35), No. 4, April 2016, pp. 1013-1024.
IEEE DOI 1604
diagnostic radiography BibRef

Hogeweg, L., Sanchez, C.I., Maduskar, P., Philipsen, R., Story, A., Dawson, R., Theron, G., Dheda, K., Peters-Bax, L., van Ginneken, B.,
Automatic Detection of Tuberculosis in Chest Radiographs Using a Combination of Textural, Focal, and Shape Abnormality Analysis,
MedImg(34), No. 12, December 2015, pp. 2429-2442.
IEEE DOI 1601
diagnostic radiography BibRef

Xu, C.[Chao], Zhou, D.X.[Dong-Xiang], Guan, T.[Tao], Zhai, Y.P.[Yong-Ping], Liu, Y.H.[Yun-Hui],
Automatic Recognition of Mycobacterium Tuberculosis Based on Active Shape Model,
IEICE(E99-D), No. 4, April 2016, pp. 1162-1171.
WWW Link. 1604
BibRef

Santosh, K.C., Antani, S.,
Automated Chest X-Ray Screening: Can Lung Region Symmetry Help Detect Pulmonary Abnormalities?,
MedImg(37), No. 5, May 2018, pp. 1168-1177.
IEEE DOI 1805
Feature extraction, Histograms, Image edge detection, Lungs, Shape, Sociology, Automation, chest X-rays, lung region symmetry, tuberculosis BibRef

Chithra, R.S., Jagatheeswari, P.,
Fractional crow search-based support vector neural network for patient classification and severity analysis of tuberculosis,
IET-IPR(13), No. 1, January 2019, pp. 108-117.
DOI Link 1812
BibRef

Mithra, K.S., Emmanuel, W.R.S.[W. R. Sam],
Automated identification of mycobacterium bacillus from sputum images for tuberculosis diagnosis,
SIViP(13), No. 8, November 2019, pp. 1585-1592.
WWW Link. 1911
BibRef

Chithra, R.S., Jagatheeswari, P.,
Severity detection and infection level identification of tuberculosis using deep learning,
IJIST(30), No. 4, 2020, pp. 994-1011.
DOI Link 2011
adaptive thresholding, deep CNN, deep learning, segmentation, severity analysis, TB BibRef

Pavani, P.G.[P. Geetha], Biswal, B.[Birendra], Sairam, M.V.S., Subrahmanyam, N.B.[N. Bala],
A semantic contour based segmentation of lungs from chest x-rays for the classification of tuberculosis using Naïve Bayes classifier,
IJIST(31), No. 4, 2021, pp. 2189-2203.
DOI Link 2112
Chan-Vese active contour, Naïve Bayes classifier (NBC), posterior anterior chest radiograph (PACR), tuberculosis (TB) BibRef

Zaidi, S.Z.Y.[S. Zainab Yousuf], Akram, M.U.[M. Usman], Jameel, A.[Amina], Alghamdi, N.S.[Norah Saleh],
A deep learning approach for the classification of TB from NIH CXR dataset,
IET-IPR(16), No. 3, 2022, pp. 787-796.
DOI Link 2202
BibRef

Morís, D.I.[Daniel I.], de Moura, J.[Joaquim], Novo, J.[Jorge], Ortega, M.[Marcos],
Unsupervised contrastive unpaired image generation approach for improving tuberculosis screening using chest X-ray images,
PRL(164), 2022, pp. 60-66.
Elsevier DOI 2212
Tuberculosis, Chest X-ray, Deep learning, Biomedical imaging, Contrastive unpaired translation, Data scarcity BibRef

Liu, Y.[Yun], Wu, Y.H.[Yu-Huan], Zhang, S.C.[Shi-Chen], Liu, L.[Li], Wu, M.[Min], Cheng, M.M.[Ming-Ming],
Revisiting Computer-Aided Tuberculosis Diagnosis,
PAMI(46), No. 4, April 2024, pp. 2316-2332.
IEEE DOI 2403
Tuberculosis, Transformers, Image classification, X-ray imaging, Medical diagnostic imaging, Deep learning, Feature extraction, symmetric positional encoding BibRef


Abdul Jalil, I., Abdul Rasam, A.R.,
Social Network Analysis of Spatial Human Mobility Behaviour In Infectious Disease Interaction: An Exploratory Evidence of Tuberculosis In Malaysia,
ISPRS21(B4-2021: 55-61).
DOI Link 2201
BibRef

Lewis, A.[Ashia], Mahmoodi, E.[Evanjelin], Zhou, Y.Y.[Yu-Yue], Coffee, M.[Megan], Sizikova, E.[Elena],
Improving Tuberculosis (TB) Prediction using Synthetically Generated Computed Tomography (CT) Images,
CVAMD21(3258-3266)
IEEE DOI 2112
Microorganisms, Image analysis, Infectious diseases, Computed tomography, Pulmonary diseases BibRef

Nkouanga, H.Y.[Hermann Y.], Vajda, S.[Szilárd],
Automatic Tuberculosis Detection Using Chest X-ray Analysis With Position Enhanced Structural Information,
ICPR21(6439-6446)
IEEE DOI 2105
Training, Laplace equations, Sociology, Semantics, Lung, Africa, Feature extraction BibRef

Das, D.[Dipayan], Santosh, K.C., Pal, U.[Umapada],
Inception-based Deep Learning Architecture for Tuberculosis Screening using Chest X-rays,
ICPR21(3612-3619)
IEEE DOI 2105
Deep learning, Solid modeling, Analytical models, Design automation, Computational modeling, Face recognition, CNN BibRef

Oloko-Oba, M.[Mustapha], Viriri, S.[Serestina],
Pre-trained Convolutional Neural Network for the Diagnosis of Tuberculosis,
ISVC20(II:558-569).
Springer DOI 2103
BibRef

Gao, X., Comley, R., Khan, M.H.M.,
An Enhanced Deep Learning Architecture for Classification of Tuberculosis Types From CT Lung Images,
ICIP20(2486-2490)
IEEE DOI 2011
Software, Indexes, Diseases, deep learning, Tuberculosis classification, CT lung images, 3D image analysis BibRef

Oloko-Oba, M.[Mustapha], Viriri, S.[Serestina],
Tuberculosis Abnormality Detection in Chest X-rays: A Deep Learning Approach,
ICCVG20(121-132).
Springer DOI 2009
BibRef

Oloko-Oba, M.[Mustapha], Viriri, S.[Serestina],
Diagnosing Tuberculosis Using Deep Convolutional Neural Network,
ICISP20(151-161).
Springer DOI 2009
BibRef

Liu, Y., Wu, Y., Ban, Y., Wang, H., Cheng, M.,
Rethinking Computer-Aided Tuberculosis Diagnosis,
CVPR20(2643-2652)
IEEE DOI 2008
X-ray imaging, Feature extraction, Detectors, Machine learning, Lung, Standards, Training BibRef

Seyedalizadeh, N., Alesheikh, A.A., Ahmadkhani, M.,
Spatio-statistical Modeling of Human Brucellosis Using Environmental Parameters: a Case Study of Northern Iran,
SMPR19(969-973).
DOI Link 1912
BibRef

El-Melegy, M.[Moumen], Mohamed, D.[Doaa], ElMelegy, T.[Tarek],
Automatic Detection of Tuberculosis Bacilli from Microscopic Sputum Smear Images Using Faster R-CNN, Transfer Learning and Augmentation,
IbPRIA19(I:270-278).
Springer DOI 1910
BibRef

Liu, C., Cao, Y., Alcantara, M., Liu, B., Brunette, M., Peinado, J., Curioso, W.,
TX-CNN: Detecting tuberculosis in chest X-ray images using convolutional neural network,
ICIP17(2314-2318)
IEEE DOI 1803
Computational modeling, Convolutional neural networks, Machine learning, Medical diagnostic imaging, Training, tuberculosis diagnosis BibRef

Sharma, U.[Utkarsh], Lall, B.[Brejesh],
Computer Aided Diagnosis of Pleural Effusion in Tuberculosis Chest Radiographs,
CIAP17(I:617-625).
Springer DOI 1711
BibRef

Makkapati, V.V.[Vishnu V.], Agrawal, R.[Ravindra], Acharya, R.[Raviraja],
Segmentation and classification of tuberculosis bacilli from ZN-stained sputum smear images,
CASE09(217-220).
WWW Link. 0908
BibRef

Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Ribs, Chest X-Rays .


Last update:Mar 16, 2024 at 20:36:19