The paper is dedicated to the evaluation of the accuracy of rotary parts produced with the use of advanced manufacturing technology. The authors investigated the impact of the layer thickness of the applied material and the orientation of the model when printing using the PolyJet method™ on the geometrical quality of manufactured products. To analyze the influence of the assumed factors on the geometrical quality of the holes, a novel evaluation method has been developed. The proposed method takes into account parameters such as roundness deviation, profile irregularity coefficient, dominant harmonic component of the roundness profile, cylindricity deviation, diameter error, and surface topography parameters. The study presented in this paper had two main objectives. The former was to analyze the impact of the layer thickness of the applied material and the orientation of the model when printing using the PolyJet method™ on the geometrical quality of rotary parts. The latter objective was to test a novel, multi-parametric method of evaluation of the accuracy of produced parts in practice. The results obtained by the authors prove that the new evaluation method can be useful in the assessment of the accuracy of manufactured products.
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http://dx.doi.org/10.1007/s00170-022-09838-1 | DOI Listing |
Comput Med Imaging Graph
December 2024
School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, Beijing, PR China; Zhengzhou Research Institute, Beijing Institute of Technology, Zhengzhou, 450000, Henan, PR China. Electronic address:
In skull base surgery, the method of using a probe to draw or 3D scanners to acquire intraoperative facial point clouds for spatial registration presents several issues. Manual manipulation results in inefficiency and poor consistency. Traditional registration algorithms based on point clouds are highly dependent on the initial pose.
View Article and Find Full Text PDFBMC Med Imaging
January 2025
Department of Information, Third Affiliated Hospital of Naval Medical University, No. 225 Changhai Road, Yangpu District, 200438, Shanghai, China.
Purpose: To develop an end-to-end convolutional neural network model for analyzing hematoxylin and eosin(H&E)-stained histological images, enhancing the performance and efficiency of nuclear segmentation and classification within the digital pathology workflow.
Methods: We propose a dual-mechanism feature pyramid fusion technique that integrates nuclear segmentation and classification tasks to construct the HistoNeXt network model. HistoNeXt utilizes an encoder-decoder architecture, where the encoder, based on the advanced ConvNeXt convolutional framework, efficiently and accurately extracts multi-level abstract features from tissue images.
Polymers (Basel)
December 2024
Fraunhofer Institute for Manufacturing Engineering and Automation IPA, Universitaetsstrasse 9, 95447 Bayreuth, Germany.
High Speed Sintering (HSS) is an additive manufacturing process with great potential to produce complex, high-quality polymer parts on an industrial scale. However, little information is currently available on the characteristics of the powder materials used and the part properties that can be achieved. This is also the case for the standard material polyamide 12 (PA 12) and the first commercially available HSS machine, the VX200 HSS.
View Article and Find Full Text PDFMaterials (Basel)
December 2024
Faculty of Materials Science and Engineering, Warsaw University of Technology, Woloska 141, 02-507 Warsaw, Poland.
This paper presents the results of a pilot application of Powder-Bed Fusion of Metals Using a Laser (PBF-LB/M) for the fabrication of M300 (1.2709) maraging steel sheet metal bending tools. S235 steel was used as a substrate for the fabrication of bending punches.
View Article and Find Full Text PDFBioengineering (Basel)
December 2024
Department of Information Engineering, University of Florence, 50139 Florence, Italy.
Image registration is a crucial post-processing technique in biomedical imaging, enabling the alignment and integration of images from various sources to facilitate accurate diagnosis, treatment planning, and longitudinal studies. This paper explores the application of Scale Invariant Feature Transform (SIFT), a robust feature-based method for the alignment of biomedical images. SIFT is particularly advantageous due to its invariance to scale, rotation, and affine transformations, making it well-suited for handling the diverse and complex nature of biomedical images.
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