Geri Dön

Supervised and interactive image segmentation techniques with an application to prostate cancer

Başlık çevirisi mevcut değil.

PDF İndir

  1. Tez No: 402208
  2. Yazar: YUSUF OĞUZHAN ARTAN
  3. Danışmanlar: DR. IMAM SAMIL YETIK
  4. Tez Türü: Doktora
  5. Konular: Üroloji, Urology
  6. Anahtar Kelimeler: Belirtilmemiş.
  7. Yıl: 2013
  8. Dil: İngilizce
  9. Üniversite: Illinois Institute of Technology
  10. Enstitü: Yurtdışı Enstitü
  11. Ana Bilim Dalı: Belirtilmemiş.
  12. Bilim Dalı: Belirtilmemiş.
  13. Sayfa Sayısı: 139

Özet

Özet yok.

Özet (Çeviri)

Prostate cancer is a leading cause of cancer death for men in the United States. Fortunately, the survival rate for early diagnosed patients is relatively high. Accurate prostate cancer localization with noninvasive imaging using MRI can be used to guide biopsy, radiotherapy, and surgery as well as to monitor disease progression. However, in general, a single type of MRI is not sufficient for reliable tumor localization. As an alternative, multispectral MRI, i.e., the use of multiple MRI-derived datasets, has emerged as a promising noninvasive imaging technique for the localization of prostate cancer; however almost all studies are with human readers. There is a significant inter and intra-observer variability for human readers, and it is substantially difficult for humans to analyze the large dataset of multispectral MRI. To solve these problems, this thesis presents various novel supervised and semi- supervised (interactive) segmentation techniques. Initially, we develop a supervised segmentation method by combining conditional random fields (CRF) and support vector machines (SVM) with a cost-sensitive framework, and show that proposed method further improves classical and cost-sensitive SVM results by incorporating spatial information. Next, we propose an extension of popular semi-supervised seg- mentation method, namely random walker (RW) algorithm, with automated seed initialization for multispectral MRI images. We also present an automated shape and boundary based segmentation approach for prostate segmentation from T2-weighted MRI. Proposed method is based on a banded geocuts algorithm that utilizes bound- ary and shape information to yield prostate segmentation. Finally, we develop a novel method that has the ability to design classifiers obtained from one imaging protocol and/or MRI device to be used on a dataset from another protocol and/or imaging device. In order to evaluate the performance of the proposed methods, we utilize multispectral MRI datasets acquired from 21 biopsy-confirmed cancer patients. Our results show that multispectral MRI helps to increase the accuracy of prostate cancer localization when compared to single MR images; and that using advanced proposed methods for prostate cancer localization performs better than available methods in the literature.

Benzer Tezler

  1. Tez No

    547238

    Yüksek mekansal çözünürlüklü uydu/uçak platformlu görüntüler ve CBS teknolojisi kullanılarak Van-Erciş depremi sonrası bina hasar tespiti

    Determination of building damage after Van-Ercis earthquake by using very high resolution satellite/aircraft platforms and GIS technology

    ASLI SABUNCU

    Doktora

    Türkçe

    Türkçe

    2018

    Jeodezi ve Fotogrametriİstanbul Teknik Üniversitesi

    Geomatik Mühendisliği Ana Bilim Dalı

    PROF. DR. AYŞE FİLİZ SUNAR

  2. Tez No

    389359

    Yüksek çözünürlüklü uydu görüntüleri kullanarak benzer spektral özelliklere sahip doğal nesnelerin ayırt edilmesine yönelik bir metodoloji geliştirme

    Developing a methodology for discriminating natural objects having spectrally similar features using very high resolution satellite imagery

    İSMAİL ÇÖLKESEN

    Doktora

    Türkçe

    Türkçe

    2015

    Jeodezi ve Fotogrametriİstanbul Teknik Üniversitesi

    Geomatik Mühendisliği Ana Bilim Dalı

    PROF. DR. TAHSİN YOMRALIOĞLU

  3. Tez No

    822488

    Forest stand segmentation with time series optical satellite imagery and superpixels

    Zaman-serisi optik uydu görüntüleri ve süperpikseller ile meşçere kuruluşlarının bölütlenmesi

    CANER DEMİRPOLAT

    Doktora

    İngilizce

    İngilizce

    2023

    Astronomi ve Uzay BilimleriOrta Doğu Teknik Üniversitesi

    Jeodezi ve Coğrafi Bilgi Teknolojileri Ana Bilim Dalı

    PROF. DR. MEHMET LÜTFİ SÜZEN

    PROF. DR. UĞUR MURAT LELOĞLU

  4. Tez No

    573710

    Extraction of vascular trees for living donated liver transplantation

    Canlı vericili karaciğer nakli için karaciğer damar ağacı bölütleme

    PARVIN BULUJU

    Yüksek Lisans

    İngilizce

    İngilizce

    2019

    Elektrik ve Elektronik MühendisliğiDokuz Eylül Üniversitesi

    Elektrik-Elektronik Mühendisliği Ana Bilim Dalı

    DOÇ. DR. MUSTAFA ALPER SELVER

  5. Tez No

    96221

    Semi-automatic video object segmentation

    Yarı-otomatik video nesne bölütleme

    ERSİN ESEN

    Yüksek Lisans

    İngilizce

    İngilizce

    2000

    Elektrik ve Elektronik Mühendisliğiİhsan Doğramacı Bilkent Üniversitesi

    Elektrik-Elektronik Mühendisliği Ana Bilim Dalı

    PROF. DR. LEVENT ONURAL

Geri Dön