A fast automated lung segmentation method for the diagnosis of lung cancer

2017 ◽  
Author(s):  
Ratishchandra Huidrom ◽  
Yambem Jina Chanu ◽  
Khumanthem Manglem Singh
Keyword(s):  
Lung Cancer ◽  
Segmentation Method ◽  
Lung Segmentation ◽  
Diagnosis Of Lung Cancer

scholarly journals An Efficient Segmentation Method for Juxtapleural Parenchyma with Modified Fractal Geometry-Based Pulmonary Boundary Detection

2019 ◽  
Vol 9 (2) ◽  
pp. 968-975
Keyword(s):  
Lung Cancer ◽  
Convex Hull ◽  
Lung Parenchyma ◽  
Adaptive Threshold ◽  
Current Approach ◽  
Segmentation Method ◽  
Computed Tomographic ◽  
Diagnosis Of Lung Cancer ◽  
Segmentation Of Images ◽  
Iteration Technique

Lung cancer seems to be the world has ever known the most leading cause of death from cancer. Early diagnosis of lung cancer will help patients significantly. The exactness of tumour form, location, and volume detection wants to play an important role to play in effective tumour treatment. Artefacts can severely deteriorate the performance or even clinically obsolete of computed tomographic (CT) images. An automatic approach to incorporate the adaptive threshold iteration technique with the segmentation of images of the lungs. The implementation involves an enhanced convex hull repair to undertake a precise lung parenchyma segmentation. The results of the analysis say with certainty that the current approach can precisely segment juxtapleural parenchymal images and that the algorithm has been put into practice and evaluated in Matlab on Windows. The investigation results indicate that the modified convex hull calculation uses only a very small number of points. The study has also shown that the algorithm proposed improves the complexity of time compared to several other algorithms

scholarly journals Improved Version of Graph-Cut Algorithm for CT Images of Lung Cancer With Clinical Property Condition

2020 ◽  
Vol 2 (4) ◽  
pp. 201-206
Author(s):  
Dr. Samuel Manoharan ◽  
Sathish
Keyword(s):  
Lung Cancer ◽  
Soft Tissues ◽  
Early Stage ◽  
Graph Cut ◽  
Lung Nodules ◽  
Lung Segmentation ◽  
Segmentation Methods ◽  
Diagnosis Of Lung Cancer ◽  
Property Condition ◽  
Task Segmentation

In a clinical evaluation, the detection of lung cancer is a challenging task. Segmentation methods are used to detect the extra growing nodule. Early diagnosis of lung cancer is significant in clinical research. The early stage of lung nodules is very soft tissues and tough to segment accurately. Generally, conservative graph cut methods are very weak to detect those soft edges in medical images. In this article, the proposed algorithm is improved to obtain the accuracy of the process to segment the edges than the conventional graph cut methods. This investigation is executed to shows the accuracy of lung segmentation.

Three-channel intelligent neoplasm classification system for the diagnosis of lung cancer

2019 ◽  
Vol 7 (3) ◽  
pp. 196-207
Author(s):  
Lev Utkin ◽  
Anna Meldo ◽  
Viktor Kryshtapovich ◽  
Viktor Tiulpin ◽  
Ernest Kasimov ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Classification System ◽  
Diagnosis Of Lung Cancer

SIALIC ACID IN THE PRIMARY AND DIFFERENTIAL DIAGNOSIS OF LUNG CANCER

2017 ◽  
Vol 63 (6) ◽  
pp. 926-932
Author(s):  
Lyudmila Belskaya ◽  
Viktor Kosenok ◽  
Ж. Массард
Keyword(s):  
Lung Cancer ◽  
Enzyme Activity ◽  
Optimization Problems ◽  
Primary Lung Cancer ◽  
Nonparametric Test ◽  
Nonsmall Cell Lung Cancer ◽  
Group Differences ◽  
Diagnosis Of Lung Cancer ◽  
And Control ◽  
Control Study

So far optimization problems for diagnostics and prognostication aids remained relevant for lung cancer as a leader in the structure of cancers. Objective: a search for regularities of changes in the saliva enzyme activity in patients with nonsmall cell lung cancer. In the case-control study, 505 people took part, divided into 2 groups: primary (lung cancer, n=290) and control (conventionally healthy, n=215). All the participants went through a questionnaire survey, saliva biochemical counts, and a histological verification of their diagnosis. The enzyme activity was measured with spectrophotometry. Between-group differences were measured with the nonparametric test. It was shown that in terms of lung cancer, we observe metabolic changes, described with the decreased de Ritis coefficient (p

Tumor Markers and Lung Cancer: Correlation between Serum and Bronchial Secretion Levels of Cea, Tpa, Canag Ca-50, Nse and Ferritin

1987 ◽  
Vol 2 (3) ◽  
pp. 151-156 ◽  
Author(s):  
Vincenzo Macchia ◽  
Angela Mariano ◽  
Mariarita Cavalcanti ◽  
Anna Coppa ◽  
Ciriaco Cecere ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cell Carcinoma ◽  
Simultaneous Determination ◽  
Neuron Specific Enolase ◽  
Bronchial Secretion ◽  
Lung Malignancy ◽  
Ca 50 ◽  
Oat Cell Carcinoma ◽  
Diagnosis Of Lung Cancer

The levels of carcinoembryonic antigeny (CEA), tissue polypeptide antigeny (TPA), CanAg 50, neuron specific enolase (NSE) and ferritin were determined in bronchial secretion and serum of patients with neoplastic and non-neoplastic lung diseases. Simultaneous determination of two or three markers in the serum and in bronchoalveolar lavage (BAL) may be clinically useful for the diagnosis of lung cancer and even for the type of tumor. The positivity of CEA determined simultaneously in serum and in BAL of patients with lung cancer is higher than 80% whereas in patients with benign lung disease it is lower than 40%. The simultaneous assay of TP A in serum and in BAL showed 100% positivity in patients with oat-cell carcinoma, the frequencies of positivity were similar in patients with non-oat-cell carcinoma. For NSE and CanAg CA-50 patients with oat-cell carinoma showed 100% positivity. Simultaneous assay of ferritin in serum and in BAL gave 85% positivity in patients with oat-cell carcinoma and only 23% in patients with non-oat-cell carcinoma. We conclude that the simultaneous determination of CEA and CanAg CA-50 or NSE in serum and in BAL is a useful aid in the diagnosis of lung malignancy.

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