Informatics Publishing Limited

Z. Faizal Khan ¹, V. Kavitha ²

Affiliations
1 Anna University of Technology, Tirunelveli, IN
2 University College of Engineering, Nagercoil Campus, Anna University of Technology, Tirunelveli, IN

Abstract

Computerized Detection of Lung cancer has been widely used for the last two decades. Image processing techniques provide a good tool for improving the manual screening of CT samples of lung. Processing of pulmonary X-ray computed tomography (CT) images is a predecessor to most of the pulmonary image analysis applications such as cancer and TB detection. The automated extraction of the lung cancer in CT images is the most crucial step in a computer-aided diagnosis (CAD) system. The CAD system is equipped with functions that automatically detect the suspicious regions from chest CT images from the Region of Interest. Significant advancements have been made in this area for the last few years. Automating the analysis of such CT data is a necessary task. This automation has created a rapidly developing research area in the field of medical imaging. This paper presents a state of art survey of various image processing methods and techniques for computerized detection of lung cancer in CT images. This paper focuses on various CAD methods for lung cancer detection such as the Lung Segmentation, Segmentation of Airways, vessels and the Segmentation of the Lobes and Fissures. In addition, research directions and future challenges focusing towards a better CAD scheme was also discussed.

Keywords

Computer-Aided Diagnosis, Lung Cancer, Lung Lobes, Fissures, Pulmonary Embolism, Image Segmentation.

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Veeramalai Sankaradass ¹, Z. Faizal Khan ², G. Suresh ¹

Affiliations
1 Department of Computer Science and Engineering, Vel Tech High Tech Dr. Rangarajan Dr. Sakunthala Engineering College, Chennai – 600062, IN
2 Department of Computer and Network Engineering, College of Engineering, Shaqra University, SA

Abstract

This research work discusses about the tracking system and also recognizing gestures using Tracking-Learning-Detection (TLD) for camera based multi-touch technology. The tracked fingers are assigned unique IDs, and the information about the finger movements are passed to the TUIO protocol. This enables us to have a communication channel between the screen elements and the touch input. A novel and low-cost approach for tracking objects is discussed. This proposed works facilitate to remove the noise by image processing technique. In this research concluded that, the issue of the touch input technologies is large and the implementation has been fulfilled, and also relatively cheap device was built successfully.

Keywords

Gestures Recognizing, Image Processing, Multi Touch, Tracking System

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