scholarly journals The Additional Filter and Ion Chamber Sensor Combination for Reducing Patient Dose in Digital Chest X-ray Projection

2015 ◽  
Vol 9 (3) ◽  
pp. 175-181 ◽  
Author(s):  
Jinsoo Lee ◽  
Changsoo Kim
Keyword(s):  
Patient Dose ◽  
X Ray ◽  
Ion Chamber ◽  
Additional Filter ◽  
Digital Chest ◽  
Chest X Ray ◽  
Ray Projection

scholarly journals Automated chest radiograph diagnosis: A Twofer for Tuberculosis and Covid-19

2020 ◽  
Author(s):  
Mitushi Verma ◽  
Deepak Patkar ◽  
Madhura Ingalharikar ◽  
Amit Kharat ◽  
Pranav Ajmera ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
X Ray ◽  
Recent Onset ◽  
Radiology Reports ◽  
Fast Spreading ◽  
Digital Chest ◽  
Chest X Ray ◽  
End To End ◽  
The Times

AbstractCoronavirus disease (Covid 19) and Tuberculosis (TB) are two challenges the world is facing. TB is a pandemic which has challenged mankind for ages and Covid 19 is a recent onset fast spreading pandemic. We study these two conditions with focus on Artificial Intelligence (AI) based imaging, the role of digital chest x-ray and utility of end to end platform to improve turnaround times. Using artificial intelligence assisted technology for triage and creation of structured radiology reports using an end to end platform can ensure quick diagnosis. Changing dynamics of TB screening in the times of Covid 19 pandemic have resulted in bottlenecks for TB diagnosis. The paper tries to outline two types of use cases, one is COVID-19 screening in a hospital-based scenario and the other is TB screening project in mobile van setting and discusses the learning of these models which have both used AI for prescreening and generating structured radiology reports.

scholarly journals Lung X-ray Segmentation using Deep Convolutional Neural Networks on Contrast-Enhanced Binarized Images

Mathematics ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 545 ◽  
Author(s):  
Hsin-Jui Chen ◽  
Shanq-Jang Ruan ◽  
Sha-Wo Huang ◽  
Yan-Tsung Peng
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Deep Convolutional Neural Networks ◽  
X Ray ◽  
Processing Approach ◽  
Segmentation Accuracy ◽  
Enhancement Method ◽  
Digital Chest ◽  
Chest X Ray ◽  
Model Training

Automatically locating the lung regions effectively and efficiently in digital chest X-ray (CXR) images is important in computer-aided diagnosis. In this paper, we propose an adaptive pre-processing approach for segmenting the lung regions from CXR images using convolutional neural networks-based (CNN-based) architectures. It is comprised of three steps. First, a contrast enhancement method specifically designed for CXR images is adopted. Second, adaptive image binarization is applied to CXR images to separate the image foreground and background. Third, CNN-based architectures are trained on the binarized images for image segmentation. The experimental results show that the proposed pre-processing approach is applicable and effective to various CNN-based architectures and can achieve comparable segmentation accuracy to that of state-of-the-art methods while greatly expediting the model training by up to 20.74 % and reducing storage space for CRX image datasets by down to 94.6 % on average.

Digital Chest X-ray with Computer-aided Detection for TB Screening within Correctional Facilities

2021 ◽  
Author(s):  
Kavindhran Velen ◽  
Farzana Sathar ◽  
Christopher J Hoffmann ◽  
Harry Hausler ◽  
Amanda Fononda ◽  
...  
Keyword(s):  
Correctional Facilities ◽  
Computer Aided Detection ◽  
X Ray ◽  
Computer Aided ◽  
Digital Chest ◽  
Chest X Ray

Symptom and digital chest X-ray TB screening in South African prisons: yield and cost-effectiveness

2020 ◽  
Vol 24 (3) ◽  
pp. 295-302 ◽  
Author(s):  
H-Y. Kim ◽  
V. Zishiri ◽  
L. Page-Shipp ◽  
S. Makgopa ◽  
G. J. Churchyard ◽  
...  
Keyword(s):  
Cost Effectiveness ◽  
South African ◽  
Correctional Facilities ◽  
Cost Effectiveness Ratio ◽  
X Ray ◽  
Symptom Screening ◽  
Night Sweats ◽  
Digital Chest ◽  
Chest X Ray ◽  
Optimal Approach

BACKGROUND: Correctional inmates are at a high risk of tuberculosis (TB). The optimal approach to screening this population is unclear.METHODS: We retrospectively reviewed records from TB screening in 64 correctional facilities in South Africa between January 2015 and July 2016. Inmates received symptom screening (any of cough, fever, weight loss, or night sweats) combined with digital chest X-ray (CXR), when available. CXRs were assessed as ‘abnormal' or with no abnormalities. Inmates with either a symptom or an ‘abnormal' CXR were asked to provide a single spot sputum for Xpert® MTB/RIF testing. We estimated the incremental cost-effectiveness ratio (ICER) per additional TB case detected using CXR screening among asymptomatic inmates.RESULTS: Of 61 580 inmates, CXR screening was available for 41 852. Of these, 19 711 (47.1%) had TB symptoms. Among 22 141 inmates without symptoms, 1939/19 783 (9.8%) had an abnormal CXR, and 8 (1.2%) were Xpert-positive among those with Xpert tests done. Of 14 942 who received symptom screening only and had symptoms, 84% (12 616) had an Xpert result, and 105 (0.8%) were positive. The ICER for CXR screening was US$22 278.CONCLUSION: Having CXR in addition to symptom screening increased yield but added considerable cost. A major limitation of screening was the low specificity of the symptom screen.

scholarly journals A study of tube voltage for chest X-ray using CR-system : Second report : For physical characteristic of additional filter

1997 ◽  
Vol 53 (7) ◽  
pp. 1012
Author(s):  
Shigeya Shimada ◽  
Yasunobu Fukunishi ◽  
Kazuo Hatanaka ◽  
Syouji Horiuchi ◽  
Yoshitaka Nishida
Keyword(s):  
Physical Characteristic ◽  
Tube Voltage ◽  
X Ray ◽  
Additional Filter ◽  
Chest X Ray ◽  
Cr System

scholarly journals An Algorithmic Approach towards Chest X-Ray Image Enhancement by Global Histogram Equalization

2016 ◽  
Vol 3 (1) ◽  
Author(s):  
G. Raghavendra Prasad
Keyword(s):  
Medical Imaging ◽  
Image Enhancement ◽  
General Class ◽  
Bone Structure ◽  
Histogram Equalization ◽  
Algorithmic Approach ◽  
X Ray ◽  
Digital Chest ◽  
Chest X Ray ◽  
Color Depth

In medical imaging, the scope of image enhancement is highly challenging. Here digital chest x –ray image are taken in a spatial domain and enhancement of the image is done through histogram equalization method. Histogram equalization is a specific case of the more general class of histogram methods. Histogram Equalization works the best when applied to images with much higher color depth like continuos data or 16 bit gray scale images. In particular, the method can lead to better views of bone structure in X-ray images that are either over or under exposed. An algorithm is proposed to enhance the chest x-ray images using Global Histogram Equalization.

scholarly journals Digital chest X-ray through a mobile van: public private partnership to detect sputum negative pulmonary TB

2017 ◽  
Vol 10 (1) ◽  
Author(s):  
Bornali Datta ◽  
Anupama Hazarika ◽  
Hemant Deepak Shewade ◽  
Kavita Ayyagari ◽  
Ajay M. V. Kumar
Keyword(s):  
Public Private Partnership ◽  
Private Partnership ◽  
Pulmonary Tb ◽  
X Ray ◽  
Digital Chest ◽  
Chest X Ray

scholarly journals Multilayer Fractional-Order Machine Vision Classifier for Rapid Typical Lung Diseases Screening on Digital Chest X-Ray Images

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 105886-105902 ◽  
Author(s):  
Jian-Xing Wu ◽  
Pi-Yun Chen ◽  
Chien-Ming Li ◽  
Ying-Che Kuo ◽  
Neng-Sheng Pai ◽  
...  
Keyword(s):  
Machine Vision ◽  
Fractional Order ◽  
Lung Diseases ◽  
X Ray ◽  
Digital Chest ◽  
Chest X Ray
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