Analysis of Lung Tumor Detection using Various Segmentation Techniques

Mathews, Arun B.; Jeyakumar, M. K.

doi:10.1109/icict48043.2020.9112468

2020 International Conference on Inventive Computation Technologies (ICICT) 2020

DOI: 10.1109/icict48043.2020.9112468

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Analysis of Lung Tumor Detection using Various Segmentation Techniques

Arun B. Mathews

M. K. Jeyakumar

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2023

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Comparative Analysis Between Different Lung Segmentation Techniques

Bhosle¹,

Kanade²,

Bhosale³

et al. 2023

ITM Web Conf.

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For the purpose of identifying various lung illnesses, computed tomography (CT) pictures of the lung must be segmented. The most significant aspect of medical imaging is image segmentation. Via an automated process, the ROI (region of interest) is extracted. The process of segmentation separates an image into sections according to a particular interest, such as segmenting human organs or tissue. Several medical disorders can benefit from the segmented image of the lung. We specifically compared and analysed various threshold segmentation algorithms in this paper in an effort to determine which one would be the best to use moving forward with image processing. We have used Computed Tomography (CT) images of Lungs with Tuberculosis (TB) dataset from Kaggle for image processing and compared them with finely masked CT images to infer the best Threshold algorithm. We have decided to do the analysis on Threshold algorithms named as Binary Threshold, Otsu’s Threshold, and Adaptive Threshold. Comparison has been done based on performance parameters such as Accuracy, Precision, Recall Value, f1-score, etc. The results are also represented in Graphical format for better understanding of performed comparison study.

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Comparative Analysis Between Different Lung Segmentation Techniques

Bhosle¹,

Kanade²,

Bhosale³

et al. 2023

ITM Web Conf.

View full text Add to dashboard Cite

show abstract

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Analysis of Lung Tumor Detection using Various Segmentation Techniques

Cited by 1 publication

References 6 publications

Comparative Analysis Between Different Lung Segmentation Techniques

Comparative Analysis Between Different Lung Segmentation Techniques

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