Lung Cancer Diagnosis of CT-SCAN Images Using Watershed Transform
The lung cancer is one of the biggest cause of death by cancer. If the cancer is detected in early stage, it can help us with variety of treatments, cheap surgery options and decreases death rate of patient(s). If detection of lung cancer is done within time, chances of death due to this can be decreased. The death rate of patient decreases from 49% to 14%. It is considered one of the most dangerous and widely-spread disease in whole world. The cancer disease is caused by cancer cells in lungs of the patient. Detection of these cells is biggest issue faced by medical researchers. If these cells are detected earlier, chances of more effective treatment will significantly increase. In this prototype, the Computed Tomography (CT) images are used. These images are more efficient and detailed than X-ray or other conventional methods. MATLAB is one of the most widely used computer program for the examination and study of CT scanned images. This prototype work proposes a convenient and low-cost procedure to detect the cancerous cells accurately from the captured lung CT scanned images. These images are processed by various technique(s) which includes CT scanned image pre-processing and segmentation, feature extraction and classification. This will minimize human error and increase accuracy in detection.
Anita Chaudhary, Sonit Sukhraj Singh ‘Lung Cancer Detection on CT Images by Using Image Processing ‘International Conference on Computing Sciences, volume-24, issue 1, January 2012.
Prof. Samir Kumar Bandyopadhyay “Edge Detection from CT Images of Lung’’ International Journal of Engineering Science & Advanced Technology Volume - 2, Issue - 1, 34 – 37
Nihad Mesanovic, Haris Huseinagic, Matija Males, , Mislav Grgic, Emir Skejic, Muamer Smajlovic ”Automatic CT Image Segmentation of the Lungs with Region Growing Algorithm”
Sayani Nandy, Nikita Pandey “A Novel Approach of Cancerous Cells Detection from Lungs CT Scan Images’’ International Journal of Advanced Research in Computer Science and Software Engineering Volume 2, Issue 8, August 2012
Prof. Samir Kumar Bandyopadhyay “Edge Detection from Ct Images of Lung’’ International Journal Of Engineering Science & Advanced Technology Volume - 2, Issue - 1, 34 – 37
Matthew S. Brown ‘patient-specific models for lung nodule detection and surveillance in CT image’ IEEE transaction on medical imaging, volume-20, Issue 12, December 2012.
Jiangdian song ‘Lung lesion extraction using a toboggan based growing automatic segmentation approch’ IEEE transaction on medical imaging, volume-35, Issue 1, January 2016.
QinghuaJi, Ronggang Shi ‘A Novel Method of Image Segmentation Using Watershed Transformation’ International Conference on Computer Science and Network Technology, August 2011.
Nunes É.D.O., Pérez M.G., Medical Image Segmentation by Multilevel Thresholding Based on Histogram Difference, presented at 17th International Conference on Systems, Signals and Image Processing, 2010.
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.