Open Access. Powered by Scholars. Published by Universities.®

Physical Sciences and Mathematics Commons

Open Access. Powered by Scholars. Published by Universities.®

LSU Doctoral Dissertations

Computer Sciences

Artificial neural network

Publication Year

Articles 1 - 2 of 2

Full-Text Articles in Physical Sciences and Mathematics

A Modular Approach To Lung Nodule Detection From Computed Tomography Images Using Artificial Neural Networks And Content Based Image Representation, Omer Muhammet Soysal Jan 2009

A Modular Approach To Lung Nodule Detection From Computed Tomography Images Using Artificial Neural Networks And Content Based Image Representation, Omer Muhammet Soysal

LSU Doctoral Dissertations

Lung cancer is one of the most lethal cancer types. Research in computer aided detection (CAD) and diagnosis for lung cancer aims at providing effective tools to assist physicians in cancer diagnosis and treatment to save lives. In this dissertation, we focus on developing a CAD framework for automated lung cancer nodule detection from 3D lung computed tomography (CT) images. Nodule detection is a challenging task that no machine intelligence can surpass human capability to date. In contrast, human recognition power is limited by vision capacity and may suffer from work overload and fatigue, whereas automated nodule detection systems can …


Complexity And Heuristics In Ruled-Based Algorithmic Music Composition, Nigel Gwee Jan 2002

Complexity And Heuristics In Ruled-Based Algorithmic Music Composition, Nigel Gwee

LSU Doctoral Dissertations

Successful algorithmic music composition requires the efficient creation of works that reflect human preferences. In examining this key issue, we make two main contributions in this dissertation: analysis of the computational complexity of algorithmic music composition, and methods to produce music that approximates a commendable human effort. We use species counterpoint as our compositional model, wherein a set of stylistic and grammatical rules governs the search for suitable countermelodies to match a given melody. Our analysis of the complexity of rule-based music composition considers four different types of computational problems: decision, enumeration, number, and optimization. For restricted versions of the …