Comparative Analysis of Proposed Artificial Neural Network (ANN) Algorithm With Other Techniques

The mortality rate among women is increasing progressively due to cancer. Generally, women around 45 years old are vulnerable from this disease. Early detection is hope for patients to survive otherwise it may reach to unrecoverable stage. Currently, there are numerous techniques available for diagnosis of such a disease out of which mammography is the most trustworthy method for detecting early cancer stage. The analysis of these mammogram images are difficult to analyze due to low contrast and nonuniform background. The mammogram images are scanned and digitized for processing that further reduces the contrast between Region of Interest and background. Presence of noise, glands and muscles leads to background contrast variations. Boundaries of suspected tumor area are fuzzy & improper. Aim of paper is to develop robust edge detection technique which works optimally on mammogram images to segment tumor area. Output results of proposed technique on different mammogram images of MIAS database are presented and compared with existing techniques in terms of both Qualitative & Quantitative parameters.

Image enhancement to leverage the 3D morphological reconstruction of single-cell neurons

Motivation To digitally reconstruct the 3D neuron morphologies has long been a major bottleneck in neuroscience. One of the obstacles to automate the procedure is the low signal-background contrast and the large dynamic range of signal and background both within and across images. Results We developed a pipeline to enhance the neurite signal and to suppress the background, with the goal of high signal-background contrast and better within- and between image homogeneity. The performance of the image enhancement was quantitatively verified according to the different figures of merit benchmarking the image quality. Additionally, the method could improve the neuron reconstruction in approximately 1/3 of the cases, with very few cases of degrading the reconstruction. This significantly outperformed three other approaches of image enhancement. Moreover, the compression rate was increased 5 times by average comparing the enhanced to the raw image. All results demonstrated the potential of the proposed method in leveraging the neuroscience providing better 3D morphological reconstruction and lower cost of data storage and transfer. Availability The study is conducted based on the Vaa3D platform and python 3.7.9. The Vaa3D platform is available on the GitHub (https://github.com/Vaa3D). The source code of the proposed image enhancement as a Vaa3D plugin, the source code to benchmark the image quality, and the example image blocks are available under the repository of vaa3d_tools/hackathon/SGuo/imPreProcess. The original fMost images of mouse brains can be found at the BICCN’s Brain Image Library (BIL) (https://www.brainimagelibrary.org). Supplementary information Supplementary data are available at Bioinformatics online.

BIMG-03. MOLECULAR IMAGING OF GLUCOSE METABOLISM FOR INTRAOPERATIVE FLUORESCENCE GUIDANCE DURING GLIOMA SURGERY

PURPOSE This study evaluated the utility of using molecular imaging of fluorescent glucose analog 2-(N-(7-Nitrobenz-2-oxa-1,3-diazol-4-yl)Amino)-2-Deoxyglucose (2-NBDG) as a discriminatory marker for intraoperative tumor border identification in a mouse glioma model. PROCEDURES 2-NBDG and were assessed in GL261 and U251 orthotopic tumor bearing mice. Intraoperative fluorescence of 2-NBDG administered topical and intravenous in normal and tumor regions was assessed with operating microscope, handheld confocal laser scanning endomicroscope (CLE) and benchtop confocal laser scanning microscope (LSM). Additionally, 2-NBDG fluorescence in tumors was compared to 5-aminolevulinic acid-induced protoporphyrin IX fluorescence. RESULTS Intravenously administered 2-NBDG was detectable in brain tumor and absent in contralateral normal brain parenchyma on wide field operating microscopy imaging. Intraoperative and benchtop CLE showed preferential 2-NBDG accumulation in the cytoplasm of glioma cells (tumor-background ratio of 2.76±0.43). Topically administered 2-NBDG did not create a sufficient tumor-background contrast for white field operating microscopy imaging, or under benchtop LSM (tumor-background ratio 1.42 ± 0.72). However, topical 2-NBDG did create sufficient contrast to evaluate cellular tissue architecture and differentiate tumor cells from normal brain parenchyma. PpIX imaging resulted in a more specific delineation of gross tumor margins than IV or topical 2-NBDG, and a significantly higher tumor-normal brain fluorescence intensity ratio. CONCLUSION After intravenous administration, 2-NBDG selectively accumulated in the experimental brain tumors and provided bright contrast under wide field fluorescence imaging with a clinical grade operating microscope. Topical 2-NBDG was able to create a sufficient contrast to differentiate tumor from normal brain cells based on visualization of cellular architecture with CLE. 5-ALA demonstrated superior specificity in outlining tumor margins and significantly higher tumor-background contrast. Given its non-toxicity, using 2-NBDG as a topical molecular marker for noninvasive in vivo intraoperative microscopy is encouraging, and warrants further clinical evaluation.

The Influence of Image Processing and Layer-to-Background Contrast on the Reliability of Flatbed Scanner-Based Characterisation of Additively Manufactured Layer Contours

Flatbed scanners (FBSs) provide non-contact scanning capabilities that could be used for the on-machine verification of layer contours in additive manufacturing (AM) processes. Layer-wise contour deviation assessment could be critical for dimensional and geometrical quality improvement of AM parts, because it would allow for close-loop error compensation strategies. Nevertheless, contour characterisation feasibility faces many challenges, such as image distortion compensation or edge detection quality. The present work evaluates the influence of image processing and layer-to-background contrast characteristics upon contour reconstruction quality, under a metrological perspective. Considered factors include noise filtering, edge detection algorithms, and threshold levels, whereas the distance between the target layer and the background is used to generate different contrast scenarios. Completeness of contour reconstruction is evaluated by means of a coverage factor, whereas its accuracy is determined by comparison with a reference contour digitised in a coordinate measuring machine. Results show that a reliable contour characterisation can be achieved by means of a precise adjustment of image processing parameters under low layer-to-background contrast variability. Conversely, under anisotropic contrast conditions, the quality of contour reconstruction severely drops, and the compromise between coverage and accuracy becomes unbalanced. These findings indicate that FBS-based characterisation of AM layers will demand developing strategies that minimise the influence of anisotropy in layer-to-background contrast.

Captivating color: evidence for optimal stimulus design in a polymorphic prey lure

Araneid spiders use abstract color patterns to attract prey. The chromatic properties of these displays vary extensively, both within and across species, and they are frequently polymorphic. Variation is often expressed in terms of signal hue (color per se), but it is unclear precisely how attractiveness scales with this property. We assessed captures among color-manipulated females of the dimorphic jeweled spider Gasteracantha fornicata in their natural webs. The manipulation magnified the natural variation in stimulus hue independently of chroma (saturation) across a range spanning most of the color spectrum. Catch rate varied across treatments in simple accordance with how greatly stimulus hue deviated from either of the two extant phenotypes. Predictions based upon fly-perceived background contrast were unsupported despite dipterans constituting ~60 % of prey. This study isolates the importance of stimulus hue and supports the premise that extant phenotypes reside in an optimal spectral range for prey attraction.

What’s New for Clinical Whole-body MRI (WB-MRI) in the 21st Century

Whole-body MRI (WB-MRI) has evolved since its first introduction in the 1970s as an imaging technique to detect and survey disease across multiple sites and organ systems in the body. The development of diffusion-weighted MRI (DWI) has added a new dimension to the implementation of WB-MRI on modern scanners, offering excellent lesion-to-background contrast, while achieving acceptable spatial resolution to detect focal lesions 5 to 10 mm in size. MRI hardware and software advances have reduced acquisition times, with studies taking 40–50 min to complete. The rising awareness of medical radiation exposure coupled with the advantages of MRI has resulted in increased utilization of WB-MRI in oncology, paediatrics, rheumatological and musculoskeletal conditions and more recently in population screening. There is recognition that WB-MRI can be used to track disease evolution and monitor response heterogeneity in patients with cancer. There are also opportunities to combine WB-MRI with molecular imaging on PET-MRI systems to harness the strengths of hybrid imaging. The advent of artificial intelligence and machine learning will shorten image acquisition times and image analyses, making the technique more competitive against other imaging technologies.

The impact of team preferences on soccer offside judgments in laypersons: a quasi-experimental study

The present study uses a quasi-experimental design to investigate the impact of team preferences on the accuracy of offside judgments. In Experiments 1 and 2, supporters of two German soccer clubs (i.e., Borussia Dortmund and FC Schalke 04) judged offsides in artificial scenes from a match between the clubs. We expected that supporters of both clubs would less frequently report the offside position of a forward from the preferred team. The results of Experiment 1 partly confirmed the predictions. Both groups reported the offside position of a yellow forward less frequently than that of a blue forward, and this effect was much larger for supporters of Borussia Dortmund than for supporters of Schalke 04. The difference between groups could be attributed to team preferences. The weaker effect of team preference in supporters of Schalke 04 was attributed to an unexpected perceptual effect that increased the accuracy of offside judgments for blue forwards in both groups. Experiments 2 and 3 showed the presumed effect of team preferences and the perceptual effect, respectively, in isolation. In summary, the results of our experiments provide evidence for (a) an effect of team preferences and (b) an effect of shirt–background contrast on offside judgments in soccer.