Using multiple images and contours for deformable 3D-2D registration of a preoperative CT in laparoscopic liver surgery.

Purpose: Laparoscopic liver resection is a challenging procedure because of the difficulty to localise inner structures such as tumours and vessels. Augmented reality overcomes this problem by overlaying preoperative 3D models on the laparoscopic views. It requires deformable registration of the preoperative 3D models to the laparoscopic views, which is a challenging task due to the liver flexibility and partial visibility.

Mutual cineMR/RT3DUS cardiac segmentation.

We present a new method to segment a cardiac RT3D ultrasound volume by integrating the registered segmentation of a cardiac cine-MR series in short axis of the same patient. The motivation behind our method is to improve the ultrasound segmentation process by integrating a reference shape built using the cine-MR segmentation on the same patient. As a side effect we obtain a close registration of the cine MR short axis slices with respect to the ultrasound volume.

Improved Estimation of Cardiac Function Parameters Using a Combination of Independent Automated Segmentation Results in Cardiovascular Magnetic Resonance Imaging.

This work aimed at combining different segmentation approaches to produce a robust and accurate segmentation result. Three to five segmentation results of the left ventricle were combined using the STAPLE algorithm and the reliability of the resulting segmentation was evaluated in comparison with the result of each individual segmentation method. This comparison was performed using a supervised approach based on a reference method.

Enhanced imaging colonoscopy facilitates dense motion-based 3D reconstruction.

We propose a novel approach for estimating a dense 3D model of neoplasia in colonoscopy using enhanced imaging endoscopy modalities. Estimating a dense 3D model of neoplasia is important to make 3D measurements and to classify the superficial lesions in standard frameworks such as the Paris classification. However, it is challenging to obtain decent dense 3D models using computer vision techniques such as Structure-from-Motion due to the lack of texture in conventional (white light) colonoscopy.

Measuring the size of neoplasia in colonoscopy using Depth-From-Defocus.

Colonoscopy is the reference medical examination for the diagnosis and treatment of neoplasia in gastroenterology. During the examination, the expert explores the colon cavity with a gastroscope in order to detect neoplasias - abnormal growths of tissue - and to diagnose which ones could be malignant. The Paris classification of superficial neoplastic lesions is the gold standard set of criteria for this type of diagnosis.

Nonsupervised ranking of different segmentation approaches: application to the estimation of the left ventricular ejection fraction from cardiac cine MRI sequences.

A statistical methodology is proposed to rank several estimation methods of a relevant clinical parameter when no gold standard is available. Based on a regression without truth method, the proposed approach was applied to rank eight methods without using any a priori information regarding the reliability of each method and its degree of automation. It was only based on a prior concerning the statistical distribution of the parameter of interest in the database.

Comparison of different segmentation approaches without using gold standard. Application to the estimation of the left ventricle ejection fraction from cardiac cine MRI sequences.

A statistical method is proposed to compare several estimates of a relevant clinical parameter when no gold standard is available. The method is illustrated by considering the left ventricle ejection fraction derived from cardiac magnetic resonance images and computed using seven approaches with different degrees of automation. The proposed method did not use any a priori regarding with the reliability of each method and its degree of automation.