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Silletti, Alberto (2009) Dynamic shape detection and analysis of deformable structures in biomedical imaging. [Ph.D. thesis]

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Abstract (english)

The goal of this work is to discuss a three-step-approach to detect, analyze and synthesize a shape given an image, or a sequence of images. Chapter 1 discusses what is a shape. The concept of shape is fuzzy: before delving with more complex topics we need at least to agree on what we call “shape”. Chapter 2 briefly present the biological case studies we used along the work.
Chapter 3 deals with the single shape detection problem, the easiest problem one could face: given a single image with a single shape of interest, how do we design an algorithm to detect it? Chapter 4 extends the single shape detection approach to reticular shapes, a kind of shapes common in biological images. Chapter 5 extends the single shape detection approach (and its reticular analogous) to a sequence of images, exploiting the temporal coherence.
Chapter 6 analyzes the shape, developing new metrics and measures, while chapter 7 closes the work dealing with the synthesis step.
A special section is chapter 8, which covers the Toolbox we developed to detect shapes. The Toolbox is meant to provide functions reusable on a plethora of problems.
Conclusions and future works are discussed in chapter 9.

Abstract (italian)

The goal of this work is to discuss a three-step-approach to detect, analyze and synthesize a shape given an image, or a sequence of images. Chapter 1 discusses what is a shape. The concept of shape is fuzzy: before delving with more complex topics we need at least to agree on what we call “shape”. Chapter 2 briefly present the biological case studies we used along the work.
Chapter 3 deals with the single shape detection problem, the easiest problem one could face: given a single image with a single shape of interest, how do we design an algorithm to detect it? Chapter 4 extends the single shape detection approach to reticular shapes, a kind of shapes common in biological images. Chapter 5 extends the single shape detection approach (and its reticular analogous) to a sequence of images, exploiting the temporal coherence.
Chapter 6 analyzes the shape, developing new metrics and measures, while chapter 7 closes the work dealing with the synthesis step.
A special section is chapter 8, which covers the Toolbox we developed to detect shapes. The Toolbox is meant to provide functions reusable on a plethora of problems.
Conclusions and future works are discussed in chapter 9.

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EPrint type:Ph.D. thesis
Tutor:Cenedese , Angelo
Ph.D. course:Ciclo 22 > Scuole per il 22simo ciclo > INGEGNERIA DELL'INFORMAZIONE > SCIENZA E TECNOLOGIA DELL'INFORMAZIONE
Data di deposito della tesi:UNSPECIFIED
Anno di Pubblicazione:21 December 2009
Key Words:Shape detection, image analysis, computer vision, drosophila
Settori scientifico-disciplinari MIUR:Area 09 - Ingegneria industriale e dell'informazione > ING-INF/05 Sistemi di elaborazione delle informazioni
Area 09 - Ingegneria industriale e dell'informazione > ING-INF/04 Automatica
Struttura di riferimento:Dipartimenti > Dipartimento di Ingegneria dell'Informazione
Codice ID:2530
Depositato il:21 Sep 2010 12:54
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