Stress and Strain Analysis and Microstructure of Al/Cu Clad Composite Fabricated by Cold Extrusion

A five-zone describing model for extrusion of aluminum/copper clad composite was established. Stress and strain were also analyzed by finite element method. The distribution rules of grain size were researched by critical shear strain theory, and zoning phenomenon of grain size was discovered. The grain size of deformed aluminum material becomes gradually finer from center to the interface. The grain size is much fine and the critical shear strain reaches the maximum value in the interface. The grain size of copper material reduces gradually from center to both the interface and exterior surface, which is caused by the higher value of critical shear strain in the interface and exterior surface. The analysis results were verified by microstructure observation and mechanical properties test, indicating that the distribution of grain size for cold extrusion forming can be interpreted by critical shear strain theory

Generalizations of the Jaccard index and Sørensen index for assessing agreement across multiple readers in object detection and instance segmentation in biomedical imaging

Significance: Manual annotations are necessary for training supervised learning algorithms for object detection and instance segmentation. These manual annotations are difficult to acquire, noisy, and inconsistent across readers. Aim: The goal of this work is to describe and demonstrate multireader generalizations of the Jaccard and Sørensen indices for object detection and instance segmentation. Approach: The multireader Jaccard and Sørensen indices are described in terms of “calls,” “objects,” and number of readers. These generalizations reduce to the equations defined by confusion matrix variables in the two-reader case. In a test set of 50 cell microscopy images, we use these generalizations to assess reader variability and compare the performance of an object detection network (Yolov5) and an instance segmentation algorithm (Cellpose2.0) with a group of five human readers using the Mann–Whitney U-test with Bonferroni correction for multiplicity. Results: The multireader generalizations were statistically different from the mean of pairwise comparisons of readers (p Conclusions: Multireader generalizations of the Jaccard and Sørensen indices provide metrics for characterizing the agreement of an arbitrary number of readers on object detection and instance segmentation tasks.</p

How to assess background activity: introducing a histogram-based analysis as a first step for accurate one-step PET quantification

Many common PET segmentation methods for malignant lesions use surrounding background activity as a reference. To date, background has to be measured by drawing a second volume of interest (VOI) in nearby, undiseased tissue. This is time consuming as two VOIs have to be determined for each lesion. The aim of our study was to analyse whether background activity in different organs and body regions could be calculated from the tumour VOI by histogram analyses. The institutional review board waived informed consent for this retrospective study. For each of the following tumour types and areas - head and neck (neck), lung, hepatic metastasis (liver), melanoma (skin), and cervix (pelvis) - 10 consecutive patients with biopsy-proven tumours who underwent (18)F-fluorodeoxyglucose-PET in January 2012 were retrospectively selected. One lesion was selected and two readers drew a cubical VOI around the lesion (VOItumour) and over the background (VOIBG). The mean value of VOIBG was compared with the mode of the histogram, using equivalence testing with an equivalence margin of ±0.5 SUV. Inter-reader agreement was analysed for the mean background, and the mode of the VOItumour histogram was assessed using the concordance correlation coefficient. For both readers, the mode of VOItumour was equivalent to the mean of VOIBG (P<0.0001 for R1 and R2). The inter-reader agreement was almost perfect, with a concordance correlation coefficient of greater than 0.92 for both the mode of VOItumour and the mean of VOIBG. Background activity determined within a tumour VOI using histogram analysis is equivalent to separately measured mean background values, with an almost perfect inter-reader agreement. This could facilitate PET quantification methods based on background values without increasing workload