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Biomedical subjects

C Knoll

Publications and source records attributed to C Knoll.

7 recordsLinked to original sources
PubMed2001

Automatic localization of cephalometric Landmarks.

A system for automatic detection of cephalometric landmarks is presented. Landmark detection is carried out in two steps: a line detection module searches for significant, well-contrasted lines of the image, such as the jaw line or the nasal spine. The landmark detection module uses the lines located in the first module to determine the search areas and then applies a pattern detection algorithm, based on mathematical morphology techniques. Relations between landmarks and lines are determined by means of a training process. The system has been tested for the detection of 17 landmarks on 20 images: more than 90% of the landmarks are accurately identified.

Algorithms↗
PubMed2001

The invasion front of human colorectal adenocarcinomas shows co-localization of nuclear beta-catenin, cyclin D1, and p16INK4A and is a region of low proliferation.

At the invasion front of well-differentiated colorectal adenocarcinomas, the oncogene beta-catenin is found in the nuclear compartment of tumor cells. Under these conditions, beta-catenin can function as a transcription factor and thus activate target genes. One of these target genes, cyclin D1, is known to induce proliferation. However, invasion front of well-differentiated colorectal adenocarcinomas are known to be zones of low proliferation and express the cell cycle inhibitor p16INK4A. Therefore, we investigated the expression profiles of nuclear beta-catenin, cyclin D1, p16INK4A, and the Ki-67 antigen, a marker for proliferation, in serial sections of well-differentiated colorectal adenocarcinomas. Invasion fronts with nuclear beta-catenin were compared with areas from central parts of the tumors without nuclear beta-catenin, for the expression of cyclin D1, p16INK4A, and Ki-67. It was observed that expression of nuclear beta-catenin, cyclin D1, and p16INK4A at the invasion front are significantly correlated. Such areas exhibit low Ki-67 expression indicating a low rate of proliferation. Thus, in colorectal carcinogenesis the function of beta-catenin and its target gene cyclin D1 does not appear to be the induction of tumor cell proliferation. In particular, the function of cyclin D1 should be reconsidered in view of these observations.

Adenocarcinoma↗
PubMed2000

Multiresolution segmentation of three-dimensional medical images using mathematical morphology techniques.

A semi-automatic method for three-dimensional segmentation of medical images is proposed. A multiresolution representation is achieved through the application of morphological filters, which assures causality for image extrema. This allows for a compact scale space representation, in which each extremum is assigned a scale value. Interactive selection of the interesting extrema of the image is carried out, aided by this scale information and other relevant features. Extrema selected are then used as markers in three-dimensional watersheds calculation. The system has been developed and tested under low cost platforms, and can be the base for totally automatic, knowledge based segmentation systems.

Artificial Intelligence↗
PubMed1999

Deformation simulation algorithms of elastic tissues in "real-time" based in elasticity theory.

In this paper, a new deformable model based in Boundary Elements Method (BEM) is presented. This model is characterised by its robustness and high deformation calculation speed. Experiments developed show that this model could calculate elastic deformations of elastic objects composed by 150 nodes with a 15 Hz. refresh rate (minim refresh rate acceptable in real time interactive systems).

Algorithms↗
PubMed1989

[Experiences with the detection of E. coli and coliform bacteria with reference to the drinking water regulation of 1986].

After the introduction of a limiting value for coliform bacteria in the German Drinking Water Regulation from May 22, 1986 the detection of coliform bacteria has become as important as that of E. coli to indicate pathogenic Enterobacteriaceae and fecal contamination. 130 water samples from different steps of drinking water treatment and distribution have been investigated for Enterobacteriaceae, even when typical indicating marks for such as acid- and gas-formation in the enrichment media were absent. We found the total of 46 isolates of Enterobacteriaceae, among which E. coli was the most frequent one. Whereas in 7 samples with acid- and gas-formation in the enrichment media Enterobacteriaceae could not be isolated, coliform bacteria and other enterobacteriaceae were found in 6 samples without these characteristics. As our experiences have show, those 'false positive' results can be avoided by a careful identification procedure of isolated microorganisms. The hygienically much more important 'false negative' results would not be recognized in routine control of drinking water following the prescribed methods.

Enterobacteriaceae↗
PubMedDate not supplied

Computer-aided periodontal disease diagnosis using computer vision.

Periodontal diseases are the major cause of tooth loss. The study of the evolution of these diseases is crucial to achieve adequate planning and treatment. Depth probing is essential to know the periodontal disease stage. In this paper we present a new system for Computer-Aided Periodontal Disease Diagnosis using computer vision. The system automates the depth probing and incorporates a colour camera fitted together with a plastic probe that automatically and exactly obtains the depth probing measure. The system has been tested by several periodontists and with 125 teeth of different patients. The differences between the values taken by the system and two periodontists have not been significant.

Absorptiometry, Photon↗