Schulz Schou (shoeball2)

Purpose To evaluate six cerebral arterial segmentation algorithms in a set of patients with a wide range of hemodynamic characteristics to determine real-world performance. Approach Time-of-flight magnetic resonance angiograms were acquired from 33 subjects normal controls ( N = 11 ), sickle cell disease ( N = 11 ), and non-sickle anemia ( N = 11 ) using a 3 Tesla Philips Achieva scanner. Six segmentation algorithms were tested (1) Otsu's method, (2) K-means, (3) region growing, (4) active contours, (5) minimum cost path, and (6) U-net machine learning. Segmentation algorithms were tested with two region-selection methods global, which selects the entire volume; and local, which iteratively tracks the arteries. Five slices were manually segmented from each patient by two readers. UNC0224 Agreement between manual and automatic segmentation was measured using Matthew's correlation coefficient (MCC). Results Median algorithm segmentation times ranged from 0.1 to 172.9 s for a single angiogram versus 10 h for manual segmentation. Algorithms had inferior performance to inter-observer vessel-based ( p less then 0.0001 , MCC = 0.65 ) and voxel-based ( p less then 0.0001 , MCC = 0.73 ) measurements. There were significant differences between algorithms ( p less then 0.0001 ) and between patients ( p less then 0.0042 ). Post-hoc analyses indicated (1) local minimum cost path performed best with vessel-based ( p = 0.0261 , MCC = 0.50 ) and voxel-based ( p = 0.0131 , MCC = 0.66 ) analyses; and (2) higher vessel-based performance in non-sickle anemia ( p = 0.0002 ) and lower voxel-based performance in sickle cell ( p = 0.0422 ) compared with normal controls. All reported MCCs are medians. Conclusions The best-performing algorithm (local minimum cost path, voxel-based) had 9.59% worse performance than inter-observer agreement but was 3 orders of magnitude faster. Automatic segmentation was non-inferior in patients with sickle cell disease and superior in non-sickle anemia.Purpose The relevance of presampling modulation transfer function (MTF) measurements in digital mammography (DM) quality control (QC) is examined. Two studies are presented a case study on the impact of a reduction in MTF on the technical image quality score and analysis of the robustness of routine QC MTF measurements. Approach In the first study, two needle computed radiography (CR) plates with identical sensitivities were used with differences in the 50% point of the MTF ( f MTF 0.5 ) larger than the limiting value in the European guidelines ( > 10 % change between successive measurements). Technical image quality was assessed via threshold gold thickness of the CDMAM phantom and threshold microcalcification diameter of the L1 structured phantom. For the second study, presampling MTF results from 595 half-yearly QC tests of 55 DM systems (16 types, six manufacturers) were analyzed for changes from the baseline value and changes in f MTF 0.5 between successive tests. Results A reduction of 20% in f MTF 0.5 of the two CR plates was observed. There was a tendency to a lower score for task-based metrics, but none were significant. Averaging over 55 systems, the absolute relative change in f MTF 0.5 between consecutive tests (with 95% confidence interval) was 3% (2.5% to 3.4%). Analysis of the maximum relative change from baseline revealed changes of up to - 10 % for one a-Se based system and - 15 % for a group of CsI-based systems. Conclusions A limit of 10% is a relevant action level for investigation. If exceeded, then the impact on performance has to be verified with extra metrics.Among 472 patients with human immunodeficiency virus-associated cryptococcal meningitis, 16% had severe visual loss at presentation, and 46% of these were 4-week survivors and remained severely impaired. Baseline cerebrospinal fluid opening pressure ≥40 cmH2O (adjusted odds ratio [aOR], 2.56; 95% confidence interval [CI], 1.36-4.83; P = .02) and fungal burden >6.0 log10 colonies/mL (