Mapping Endometrial Implants by Registering Transvaginal Ultrasound to Pelvic Magnetic Resonance Images
pelvik manyetik rezonans görüntülerine transvajinal ultrason kaydedilerek endometrial implantların haritalanması
- Tez No: 739875
- Danışmanlar: PROF. DR. ADRİEN BARTOLİ
- Tez Türü: Doktora
- Konular: Bilgisayar Mühendisliği Bilimleri-Bilgisayar ve Kontrol, Computer Engineering and Computer Science and Control
- Anahtar Kelimeler: Belirtilmemiş.
- Yıl: 2014
- Dil: İngilizce
- Üniversite: Clermont Auvergne Unıversıty
- Enstitü: Yurtdışı Enstitü
- Ana Bilim Dalı: Bilgisayar Mühendisliği Ana Bilim Dalı
- Bilim Dalı: Bilgisayar Mühendisliği Bilim Dalı
- Sayfa Sayısı: Belirtilmemiş.
Özet
Depth from defocus (DFD) investigates to obtain three-dimensional depth information from images by estimating amount of the defocus in the images. The DFD technique requires only two images captured with different camera parameters such as focal length. Although the DFD avoids major problems related to stereo vision by maintaining only one point of view. However, the DFD requires precise calibration of internal camera parameters. In this thesis, a new method called Lens-based defocus calibration technique is described for determining the distance of the objects. The method involves simple local operations to obtain the depth map of the scene. In this method, the defocus level of a set of image was found by a Gaussian point spread function model and these results were used to find the accurate depth information. Then, a telecentric lens was added to the system to achieve the high pixel registration between two images. After that, the system was calibrated for a specific focus setting with the range of 700-8000mm. Consequently, the range depth accuracy was found to be 0.91%-2.6% of the actual distance of the object. Calibrated parameters yield consistent results in depth estimation and the proposed method was found to measure accurate depth maps for complicated scenes.
Özet (Çeviri)
Depth from defocus (DFD) investigates to obtain three-dimensional depth information from images by estimating amount of the defocus in the images. The DFD technique requires only two images captured with different camera parameters such as focal length. Although the DFD avoids major problems related to stereo vision by maintaining only one point of view. However, the DFD requires precise calibration of internal camera parameters. In this thesis, a new method called Lens-based defocus calibration technique is described for determining the distance of the objects. The method involves simple local operations to obtain the depth map of the scene. In this method, the defocus level of a set of image was found by a Gaussian point spread function model and these results were used to find the accurate depth information. Then, a telecentric lens was added to the system to achieve the high pixel registration between two images. After that, the system was calibrated for a specific focus setting with the range of 700-8000mm. Consequently, the range depth accuracy was found to be 0.91%-2.6% of the actual distance of the object. Calibrated parameters yield consistent results in depth estimation and the proposed method was found to measure accurate depth maps for complicated scenes.
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