Biomedical subjects

Gabriel Kiss

Publications and source records attributed to Gabriel Kiss.

5 recordsLinked to original sources

PubMed2006

Computer-aided detection of colonic polyps using low-dose CT acquisitions.

RATIONALE AND OBJECTIVES: This report proposes an alternative method for the automatic detection of colonic polyps that is robust enough to be directly applicable on low-dose computed tomographic data. MATERIALS AND METHODS: The polyp modeling process takes into account both the gray-level appearance of polyps (intensity profiles) and their geometry (extended Gaussian images). Spherical harmonic decompositions are used for comparison purposes, allowing fast estimation of the similarity between a candidate and a set of previously computed models. Starting from the original raw data (acquired at 55 mA), five patient data sets (prone and supine scans) are reconstructed at different dose levels (to 5 mA) by using different kernel filters, slice overlaps, and increments. Additionally, the efficacy of applying an edge-preserving smoothing filter before detection is assessed. RESULTS: Although image quality decreases when decreasing acquisition milliamperes, all polyps greater than 6 mm are detected successfully, even at 15 mA. Although not important at high doses, smoothing improves detection results for ultra-low-dose (tube current<15 mA) data. CONCLUSION: The advantage of low-dose scans is a significant decrease in effective dose from 4.93 to 1.61 mSv while retaining high detection values, particularly important when thinking of population screening.

Algorithms↗

PubMed2005

Computer aided detection for low-dose CT colonography.

The paper describes a method for automatic detection of colonic polyps, robust enough to be directly applied to low-dose CT colonographic datasets. Polyps are modeled using gray level intensity profiles and extended Gaussian images. Spherical harmonic decompositions ensure an easy comparison between a polyp candidate and a set of polypoid models, found in a previously built database. The detection sensitivity and specificity values are evaluated at different dose levels. Starting from the original raw-data (acquired at 55mAs), 5 patient datasets (prone and supine scans) are reconstructed at different dose levels (down to 5mAs), using different kernel filters and slice increments. Although the image quality decreases when lowering the acquisition mAs, all polyps above 6mm are successfully detected even at 15 mAs. Accordingly the effective dose can be reduced from 4.93mSv to 1.61 mSv, without affecting detection capabilities, particularly important when thinking of population screening.

Algorithms↗

PubMed2002

Dry preparation for virtual CT colonography with fecal tagging using water-soluble contrast medium: initial results.

The purpose of this study was to evaluate the feasibility of a dry bowel preparation, i.e. without laxative fluids, for virtual CT colonography (VCTC), and its impact on patient acceptance compared with conventional colonoscopy (CC). A randomly chosen patient population scheduled for CC ( n=11) was first submitted to VCTC after a dry preparation, consisting of low-residue meals combined with a small amount of a iodinated water-soluble contrast medium during each meal 3 days before VCTC. In different colon segments and between different persons, the degree of tagging in VCTC was evaluated and graded. Patient acceptance and future preference were assessed for both preparations as well as for both investigations. The mixing of the contrast with the intestinal content results in contrast impregnated stool, the tagged feces. The degree of fecal tagging was good in the majority of the patients and the colonic segments, especially in the descending colon and sigmoid. Furthermore, patient acceptance and preference were clearly in favour of VCTC compared with CC merely because of the non-invasiveness of the dry preparation. Dry bowel preparation and VCTC is a promising approach towards a patient-friendly colon cancer-screening setup.

Adult↗

PubMed2001

Computer-aided diagnosis in virtual colonography via combination of surface normal and sphere fitting methods.

The success of CT colonography (CTC) depends on appropriate tools for quick and accurate diagnostic reading. Current advancements in computer technology have the potential to bring such tools even to personal computer level. In this paper a technique for computed-aided diagnosis (CAD) using CT colonography is described. The method uses a combination of surface normal and sphere fitting methods to label positions in the volume data, which have a strong likelihood of being polyps, and presents them in a user-friendly way. The method was tested on a study group of 18 patients and the detection rate for polyps of 10 mm or larger was 100%, comparable to that of human readers. The price paid for a high detection rate was a large number of approximately eight false-positive findings per case. Our results show that CAD is feasible, and if the number of false positives is further reduced, then this method can be useful for clinical screenings.

Algorithms↗

PubMedDate not supplied

Stool tagging applied in thin-slice multidetector computed tomography colonography.

OBJECTIVE: To compare thin-slice multidetector computed tomography colonography (CTC) that uses stool tagging with colonoscopy. METHOD: One hundred fifty patients scheduled for colonoscopy underwent high-resolution CTC. An iodinated contrast agent was added to the preparation to tag the residual colonic fluid and stool. The effect of fluid tagging was assessed first. Sensitivity and specificity were calculated for two independent readers. In addition, values were recalculated separately for the first and last 75 patients. RESULTS: Tagging was optimal in 95.3% of the cases, and reader confidence was high. Sensitivities were 64.1%-66.7% (for the 2 readers) for 5- to 9-mm polyps and 91.7% for larger polyps. The overall specificity was 94.2% and 95%. Sensitivity improved during the study for both 5- to 9-mm polyps (from 54.2%-58.3% to 80%) and polyps larger than 9 mm (from 50% to 100%). Specificity changed nonuniformly. CONCLUSION: The combination of fluid tagging and high-resolution scanning in CTC showed high sensitivity and specificity, especially concerning sensitivity for polyps of 10 mm and larger.

Colon↗