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{ "item_title" : "High-Precision Rapid Prototyping", "item_author" : [" Narayana Battula "], "item_description" : "This study establishes a high-precision medical additive manufacturing framework that systematically mitigates data processing and volumetric thermal defects. Uncompensated 3D printing introduces dimensional inaccuracies via DICOM thresholding distortions and powder sintering bleed. To resolve this, we present an optimized pipeline utilizing a FORMIGA P 100 Selective Laser Sintering (SLS) system. The process standardizes data acquisition at a 0.625 mm voxel slice thickness, deploys algorithmic adaptive thresholding during segmentation, and embeds mathematical scaling variables (3.32% X, 3.36% Y, 2.2% Z axis expansion) directly into the print-preparation engine. Quantitative evaluation of the sintered polyamide mandibles demonstrated supreme dimensional fidelity. When deployed in clinical workflows, these true-to-scale bio-models reduced pre-fit template and hardware adaptation times, lowering surgical execution duration by 26%. This validated framework provides a scalable mathematical foundation for automated machine learning segmentation and 4D responsive biomaterials.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/6/63/048/734/6630487346_b.jpg", "price_data" : { "retail_price" : "101.00", "online_price" : "101.00", "our_price" : "101.00", "club_price" : "101.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
High-Precision Rapid Prototyping|Narayana Battula

High-Precision Rapid Prototyping

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Overview

This study establishes a high-precision medical additive manufacturing framework that systematically mitigates data processing and volumetric thermal defects. Uncompensated 3D printing introduces dimensional inaccuracies via DICOM thresholding distortions and powder sintering bleed. To resolve this, we present an optimized pipeline utilizing a FORMIGA P 100 Selective Laser Sintering (SLS) system. The process standardizes data acquisition at a 0.625 mm voxel slice thickness, deploys algorithmic adaptive thresholding during segmentation, and embeds mathematical scaling variables (3.32% X, 3.36% Y, 2.2% Z axis expansion) directly into the print-preparation engine. Quantitative evaluation of the sintered polyamide mandibles demonstrated supreme dimensional fidelity. When deployed in clinical workflows, these true-to-scale bio-models reduced pre-fit template and hardware adaptation times, lowering surgical execution duration by 26%. This validated framework provides a scalable mathematical foundation for automated machine learning segmentation and 4D responsive biomaterials.

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Details

  • ISBN-13: 9786630487343
  • ISBN-10: 6630487346
  • Publisher: LAP Lambert Academic Publishing
  • Publish Date: September 2026
  • Dimensions: 9 x 6 x 0.38 inches
  • Shipping Weight: 0.5 pounds
  • Page Count: 164

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