MIPAR Image Analysis
@MIPAR_Software
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Revolutionary image analysis software, capable of identifying and measuring features from nearly any image one can capture.
Columbus, OH
Joined October 2015
MIPAR performs sub-pixel CD metrology using adaptive edge extraction to measure linewidth, pitch, and critical features in SEM images. Learn more at https://t.co/8LyQZ5AzPn
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Within MIPAR you can construct a fully automated “recipe” mixing cleanup, FFT-normalization, convolution filters and ML-enabled segmentation — then export it via API into a Python pipeline. Learn more at https://t.co/ABGuSyjeF5
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Automated boundary extraction quantifies grain size and morphology in multiphase alloys. Learn more at https://t.co/AnJfolzQQI
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MIPAR automates radial unwrapping of Petri dish images for illumination-corrected colony segmentation and morphology-based enumeration. Learn more at https://t.co/SlrBbQessO
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Automating microstructural workflows, MIPAR integrates deep learning segmentation with rule-based recipes for reproducible quantitative analysis. Learn more at https://t.co/Sfn41BfNBi
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MIPAR quantifies pore size distribution by segmenting pores, extracting morphology metrics, and generating cumulative and differential distributions. Learn more at https://t.co/RrgS4jbnoO
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MIPAR enables automated quantification of whole-slide pathology images, integrating deep learning segmentation with reproducible pipelines for histological feature extraction. Learn more at https://t.co/qVIXV76vxs
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Quantify powder morphology with MIPAR: automated particle size and shape analysis yields reproducible metrics for distribution, aspect ratio, and sphericity. Learn more at https://t.co/nEdC9zGH3w
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MIPAR automates phase segmentation in metallography, quantifying phase fractions and morphologies directly from micrographs. Learn more at https://t.co/CTljrM9YPu
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MIPAR deep learning models segment contaminants across diverse substrates, enabling precise quantification of inclusion morphology and spatial distribution. Learn more at https://t.co/2ishlW4ox4
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Automate segmentation of overlapping colonies in Petri dish images using thresholding, watershed, and circularity filters. Learn more at https://t.co/SlrBbQessO
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Cell segmentation with MIPAR leverages local contrast and shape-based filtering to isolate overlapping, irregular, or faint cell boundaries in complex biological images. Learn more at https://t.co/NSJHZsv8dT
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Quantify porosity and pore size distribution across scales using MIPAR's automated segmentation and measurement tools. Ideal for membrane, scaffold, and foam analysis. Learn more at https://t.co/duhwN2LmQT
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AI-powered segmentation in MIPAR enables high-throughput phenotypic quantification of cell morphology across diverse imaging modalities. Learn more at https://t.co/nj04MYjUbr
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Automated segmentation in MIPAR accelerates digital histology by quantifying structures in high-resolution slides with reproducible precision. Learn more at https://t.co/oQNyfsdnWc
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MIPAR enables precise terrain classification and feature extraction from drone-captured orthomosaics using pixel-level segmentation and batch processing. Learn more at https://t.co/rboX2dWGQK
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Die-to-die overlay error detection using MIPAR enables sub-micron misalignment quantification across wafers, supporting high-precision yield improvement. Learn more at https://t.co/xQawxfLsv4
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MIPAR segments complex microstructures to quantify grain boundaries, inclusions, and phase areas in heterogeneous materials. Learn more at https://t.co/iMOpXhzs6E
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MIPAR AI-aided thermal imaging segments rail defects, flags fires/obstacles from drone views, enhancing high-speed safety. Learn more at https://t.co/77OISYtA6y
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MIPAR DL meets ASTM E112, auto-segments grains and outputs size distributions plus reports for metals and ceramics. Learn more at https://t.co/ML3kYvJwjH
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