Lung Segmentation using Python
Soham Deshmukh, Milind Rane , Aarya Deshmukh, Akanksha Deshmukh, Om Deshmukh
Lung Segmentation, Computed Tomography (CT), Medical Imaging, Convolutional Neural Network (CNN), Deep Learning, Image Processing, Segmentation Masks,2D/3D Segmentation, Data Preprocessing, Medical Image Analysis.
— This paper presents a lung segmentation system for computed tomography (CT) scans using Python. The system is built upon a custom dataset class that integrates essential functionalities for loading and preprocessing medical imaging data. The dataset class incorporates methods for accessing CT scans and corresponding lung masks, enabling the preparation of data for segmentation tasks. Furthermore, the system accommodates various segmentation scenarios by adjusting the masks based on specified classes, enhancing its adaptability to different classification requirements. Notably, it employs advanced techniques, including image resizing and intensity normalization, crucial for model training and performance optimization. The proposed lung segmentation system is a versatile tool equipped to handle diverse CT imaging datasets, demonstrating potential applicability in aiding medical professionals in precise lung tissue delineation for diagnostic and treatment purposes in pulmonary healthcare.
Article Details
Unique Paper ID: 163949

Publication Volume & Issue: Volume 10, Issue 12

Page(s): 2252 - 2258
Article Preview & Download

Share This Article

Join our RMS

Conference Alert

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024

Last Date: 15th March 2024

Call For Paper

Volume 11 Issue 1

Last Date for paper submitting for Latest Issue is 25 June 2024

About Us enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on

Social Media

Google Verified Reviews