M. Chlebiej

Generation of dynamic heart model based on 4d echocardiographic images

One of the most challenging problems in the modern cardiology is a correct quantification of the left ventricle contractility and synchronicity. Correct, quantitative assessment of these parameters, which could be changed in a course of many severe diseases of the heart (e.g. coronary artery disease and myocardial infarction, heart failure), is a key factor for the right diagnose and further therapy. Up to date, in clinical daily practice, most of these information is collected by transthoracic two dimensional echocardiography. Assessment of these parameters is difficult and depends on observer experience. However, quantification method of the contractility assessment based on strain and strain analysis are available, these methods still are grounded on 2D analysis. Real time 3D echocardiography gives physicians opportunity for real quantitative analysis of the left ventricle contractility and synchronicity. In this work we present a method for estimating heart motion from 4D (3D+time) echocardiographic images.

A New Image Fusion Method for Estimating 3D Surface Depth

Creation of virtual reality models from photographs is very complex and time-consuming process, that requires special equipment like laser scanners, a large number of photographs and manual interaction. In this work we present a method for generating of surface geometry of photographed scene. Our approach is based on the phenomenon of shallow depth-of-field in close-up photography. Representing such surface details is useful to increase the visual realism in a range of application areas, especially biological structures or microorganisms. For testing purposes a set of images of the same scene is taken from a typical digital camera with macro lenses with a different depth-of-field. Our new image fusion method employs discrete Fourier transform to designate sharp regions in this set of images, combine them together into a fully focused image and finally produce a height field map. Further image processing algorithms approximate three dimensional surface using this height field map and a fused image. Experimental results show that our method works for wide range of cases and gives a good tool for acquiring surfaces from a few photographs.

Modeling of 3D Scene Based on Series of Photographs Taken with Different Depth-of-Field

This paper presents a method for fusing multifocus images into enhanced depth-of-field composite image and creating a 3D model of a photographed scene. A set of images of the same scene is taken from a typical digital camera with macro lenses with different depth-of-field. The method employs convolution and morphological filters to designate sharp regions in this set of images and combine them together into an image where all regions are properly focused. The presented method consists of several phases including: image registration, height map creation, image reconstruction and final 3D scene reconstruction. In result a 3D model of the photographed object is created.

Computer-based planning of optimal donor sites for autologous osseous grafts

Bone graft surgery is often necessary for reconstruction of craniofacial defects after trauma, tumor, infection or congenital malformation. In this operative technique the removed or missing bone segment is filled with a bone graft. The mainstay of the craniofacial reconstruction rests with the replacement of the defected bone by autogeneous bone grafts. To achieve sufficient incorporation of the autograft into the host bone, precise planning and simulation of the surgical intervention is required. The major problem is to determine as accurately as possible the donor site where the graft should be dissected from and to define the shape of the desired transplant. A computer-aided method for semi-automatic selection of optimal donor sites for autografts in craniofacial reconstructive surgery has been developed. The non-automatic step of graft design and constraint setting is followed by a fully automatic procedure to find the best fitting position. In extension to preceding work, a new optimization approach based on the Levenberg-Marquardt method has been implemented and embedded into our computer-based surgical planning system. This new technique enables, once the pre-processing step has been performed, selection of the optimal donor site in time less than one minute. The method has been applied during surgery planning step in more than 20 cases. The postoperative observations have shown that functional results, such as speech and chewing ability as well as restoration of bony continuity were clearly better compared to conventionally planned operations. Moreover, in most cases the duration of the surgical interventions has been distinctly reduced.