Computer Engineering Commons^™

Analysis Of Various Classification Techniques For Computer Aided Detection System Of Pulmonary Nodules In Ct, Barath Narayanan Narayanan, Russell C. Hardie, Temesguen Messay

Russell C. Hardie

Lung cancer is the leading cause of cancer death in the United States. It usually exhibits its presence with the formation of pulmonary nodules. Nodules are round or oval-shaped growth present in the lung. Computed Tomography (CT) scans are used by radiologists to detect such nodules. Computer Aided Detection (CAD) of such nodules would aid in providing a second opinion to the radiologists and would be of valuable help in lung cancer screening. In this research, we study various feature selection methods for the CAD system framework proposed in FlyerScan. Algorithmic steps of FlyerScan include (i) local contrast enhancement (ii) …

Differential Tilt Variance Effects Of Turbulence In Imagery: Comparing Simulation With Theory, Daniel A. Lemaster, Russell C. Hardie, Szymon Gladysz, Matthew D. Howard, Michael Armand Rucci, Matthew E. Trippel, Jonathan D. Power, Barry K. Karch

Russell C. Hardie

Differential tilt variance is a useful metric for interpreting the distorting effects of turbulence in incoherent imaging systems. In this paper, we compare the theoretical model of differential tilt variance to simulations. Simulation is based on a Monte Carlo wave optics approach with split step propagation. Results show that the simulation closely matches theory. The results also show that care must be taken when selecting a method to estimate tilts.

Segmentation Of Pulmonary Nodules In Computed Tomography Using A Regression Neural Network Approach And Its Application To The Lung Image Database Consortium And Image Database Resource Initiative Dataset, Temesguen Messay, Russell C. Hardie, Timothy R. Tuinstra

Russell C. Hardie

We present new pulmonary nodule segmentation algorithms for computed tomography (CT). These include a fully-automated (FA) system, a semi-automated (SA) system, and a hybrid system. Like most traditional systems, the new FA system requires only a single user-supplied cue point. On the other hand, the SA system represents a new algorithm class requiring 8 user-supplied control points. This does increase the burden on the user, but we show that the resulting system is highly robust and can handle a variety of challenging cases. The proposed hybrid system starts with the FA system.

If improved segmentation results are needed, the SA …