Quantitative analysis for differential diagnosis of lung cancer on blood vessel connectivity using thoracic 3D CT images

2000 ◽  
Author(s):  
Akira Tanaka ◽  
Tetsuya Tozaki ◽  
Yoshiki Kawata ◽  
Noboru Niki ◽  
Hironobu Ohmatsu ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Differential Diagnosis ◽  
Quantitative Analysis ◽  
Blood Vessel ◽  
Ct Images ◽  
3D Ct ◽  
Diagnosis Of Lung Cancer

scholarly journals Reducing False-Positives in Lung Nodules Detection Using Balanced Datasets

2021 ◽  
Vol 9 ◽  
Author(s):  
Jinglun Liang ◽  
Guoliang Ye ◽  
Jianwen Guo ◽  
Qifan Huang ◽  
Shaohui Zhang
Keyword(s):  
Lung Cancer ◽  
Early Stage ◽  
Pulmonary Nodules ◽  
Ct Images ◽  
False Positives ◽  
Classification Systems ◽  
Cad System ◽  
Nodule Detection ◽  
Diagnosis Of Lung Cancer ◽  
Lung Ct

Malignant pulmonary nodules are one of the main manifestations of lung cancer in early CT image screening. Since lung cancer may have no early obvious symptoms, it is important to develop a computer-aided detection (CAD) system to assist doctors to detect the malignant pulmonary nodules in the early stage of lung cancer CT diagnosis. Due to the recent successful applications of deep learning in image processing, more and more researchers have been trying to apply it to the diagnosis of pulmonary nodules. However, due to the ratio of nodules and non-nodules samples used in the training and testing datasets usually being different from the practical ratio of lung cancer, the CAD classification systems may easily produce higher false-positives while using this imbalanced dataset. This work introduces a filtering step to remove the irrelevant images from the dataset, and the results show that the false-positives can be reduced and the accuracy can be above 98%. There are two steps in nodule detection. Firstly, the images with pulmonary nodules are screened from the whole lung CT images of the patients. Secondly, the exact locations of pulmonary nodules will be detected using Faster R-CNN. Final results show that this method can effectively detect the pulmonary nodules in the CT images and hence potentially assist doctors in the early diagnosis of lung cancer.

Automatic analysis of 3D low dose CT images for early diagnosis of lung cancer

2009 ◽  
Vol 42 (6) ◽  
pp. 1041-1051 ◽  
Author(s):  
A. El-Baz ◽  
G. Gimel’farb ◽  
R. Falk ◽  
M. Abo El-Ghar
Keyword(s):  
Lung Cancer ◽  
Early Diagnosis ◽  
Low Dose ◽  
Ct Images ◽  
Automatic Analysis ◽  
Low Dose Ct ◽  
Diagnosis Of Lung Cancer

Comparison of Differential Diagnosis of Lung Cancer by Diffuse Weighted Imaging and Sagittal Imaging with Short Inversion Recovery Sequence

2021 ◽  
Vol 11 (3) ◽  
pp. 822-826
Author(s):  
Wei Zhang ◽  
Qingyu Cai ◽  
Guoli Wei
Keyword(s):  
Lung Cancer ◽  
Differential Diagnosis ◽  
Squamous Cell ◽  
Lung Carcinoma ◽  
Small Cell Lung Carcinoma ◽  
Small Cell ◽  
Small Cell Lung ◽  
Recovery Sequence ◽  
Cell Lung Carcinoma ◽  
Diagnosis Of Lung Cancer

The differential diagnosis of advanced lung cancer is difficult in clinical practice. Our study aims to compare the value of diffusion weighted imaging (DWI) with short-term inversion recovery sequence (STIR) for sagittal imaging in the differential diagnosis of lung cancer. 149 patients with non-small cell lung carcinoma (NSCLC) were enrolled and underwent DWI and STIR sagittal imaging. To quantify cancer types, we evaluated the apparent diffusion coefficient (ADC) value on DWI and the contrast ratio (CRs) on sagittal imaging. The ADC values of subclasses in NSCLC were significantly higher than small cell lung carcinoma (SCLC) (p <0.01). The mean CRs were 1.59 for SCLC and 1.30 for NSCLC with a significant difference (p < 0.01). Large cell carcinomas (LCC) and adenocarcinomas have significant differences compared to small cell carcinomas (SCC) without difference between squamous cell carcinomas (p > 0.05); this is also the case for CRs. Squamous cell carcinoma and adenocarcinoma have significant differences compared to SCC without difference in LCC (p > 0.05). Qualitative evaluation of the feasible thresholds DWI and STIR showed that the thresholds were 0.9810−3 mm2/s and 1.37 respectively. The specificity and accuracy was 78.5% is 85.3% for DWI, which was significantly higher than STIR (56.3% and 61.0%). The combination of DWI and STIR sequences was superior to DWI alone with an accuracy rate of 94.3%. DWI is more helpful than STIR in differentiating SCLC and NSCLC, and their combined use can significantly improve diagnosis accuracy.

scholarly journals Meta-markers for the differential diagnosis of lung cancer and lung disease

2016 ◽  
Vol 148 ◽  
pp. 36-43 ◽  
Author(s):  
Yong-In Kim ◽  
Jung-Mo Ahn ◽  
Hye-Jin Sung ◽  
Sang-Su Na ◽  
Jaesung Hwang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Differential Diagnosis ◽  
Lung Disease ◽  
Diagnosis Of Lung Cancer

Tracking time interval changes of pulmonary nodules on follow-up 3D CT images via image-based risk score of lung cancer

2013 ◽  
Author(s):  
Y. Kawata ◽  
N. Niki ◽  
H. Ohmatsu ◽  
M. Kusumoto ◽  
T. Tsuchida ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Risk Score ◽  
Pulmonary Nodules ◽  
Ct Images ◽  
Time Interval ◽  
3D Ct ◽  
Tracking Time

scholarly journals From suspicion of angioedema to the diagnosis of lung cancer

Oncoreview ◽  
2020 ◽  
Vol 10 (3) ◽  
pp. 108-112
Author(s):  
Łukasz Moos ◽  
Wojciech Żurek ◽  
Katarzyna Kapeluszna ◽  
Zenon Brzoza
Keyword(s):  
Lung Cancer ◽  
Differential Diagnosis ◽  
Superior Vena Cava Syndrome ◽  
Superior Vena ◽  
Vena Cava ◽  
Small Cell ◽  
Case Presentation ◽  
Facial Swelling ◽  
Vena Cava Syndrome ◽  
Diagnosis Of Lung Cancer

Angioedema is a localized and self-limiting oedema of the subcutaneous and submucosal tissue. Case presentation: 73-year-old man was admitted to the Division of Allergology with the diagnosis of angioedema. Detailed physical examination led to the suspicion of superior vena cava syndrome with secondary face swelling. Biopsy revealed metastasis of small cell carcinoma in superclavicular lymph nodes. Conclusions: Facial swelling, especially recurrent and non-inflammatory, is often, but not always caused by angioedema. Insightful differential diagnosis is crucial before making the final one.

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