Journal: Scientific Reports

Article Title: Comparing multi-texture fibrosis analysis versus binary opacity-based abnormality detection for quantitative assessment of idiopathic pulmonary fibrosis

doi: 10.1038/s41598-025-85135-7

Figure Lengend Snippet: Exemplary results of the multi-texture lung analysis tool and the opacity-based lung analysis tool. CT in coronal view of a 62 year old patient with idiopathic pulmonary fibrosis ( A ), analyzed by the opacity-based Pneumonia tool (Siemens Healthineers), the red lines represent the segmented fibrotic areas ( B ) with additional 3D reconstruction ( C ). ( D ) Analysis with the multi-texture lung analysis tool (CALIPER, Biomedical imaging resource laboratory, Mayo Clinic) with the yellow areas representing fibrotic altered tissue.

Article Snippet: The computer-aided lung informatics for pathology evaluation and ratings (CALIPER) tool is part of the Imbio lung texture analysis software (Imbio) and was created by the Biomedical Imaging Resource Laboratory of the Mayo Clinic, Minnesota.

Techniques: Imaging

Journal: Scientific Reports

Article Title: Comparing multi-texture fibrosis analysis versus binary opacity-based abnormality detection for quantitative assessment of idiopathic pulmonary fibrosis

doi: 10.1038/s41598-025-85135-7

Figure Lengend Snippet: Linear regression analyses. Illustration of regression analysis between the opacity-based fibrotic lung (OFL) and the multi-texture fibrotic lung (MTFL) quantification, as well as regression analysis of OFL and MTFL with spirometry parameters with Pearson correlation coefficient (r) bigger than 0.25. 95% confidence intervals are indicated by light-colored areas. TLC percent predicted total lung capacity, VC percent predicted vital capacity and DL CO diffusing capacity of the lungs for carbon monoxide.

Article Snippet: The computer-aided lung informatics for pathology evaluation and ratings (CALIPER) tool is part of the Imbio lung texture analysis software (Imbio) and was created by the Biomedical Imaging Resource Laboratory of the Mayo Clinic, Minnesota.

Techniques:

Journal: Scientific Reports

Article Title: Comparing multi-texture fibrosis analysis versus binary opacity-based abnormality detection for quantitative assessment of idiopathic pulmonary fibrosis

doi: 10.1038/s41598-025-85135-7

Figure Lengend Snippet: Bland-Altman analysis. The opacity-based fibrotic lung (OFL) quantifications was compared to the multi-texture fibrotic lung (MTFL) measurements.

Article Snippet: The computer-aided lung informatics for pathology evaluation and ratings (CALIPER) tool is part of the Imbio lung texture analysis software (Imbio) and was created by the Biomedical Imaging Resource Laboratory of the Mayo Clinic, Minnesota.

Techniques:

Journal: Diagnostics

Article Title: Artificial Intelligence Unveils the Unseen: Mapping Novel Lung Patterns in Bronchiectasis via Texture Analysis

doi: 10.3390/diagnostics14242883

Figure Lengend Snippet: Lung texture analysis report: The Dicom representative image of each category of pattern. These were chosen based on the predominance of lung parenchymal patterns including hyperlucent, ground glass [GG], reticular, and honeycombing. Imbio LTA provided their regional distribution within three different lung zones [upper, middle, lower] in each lung. The platform provided an image in which each lung pattern was colored differently, allowing the evaluation of disease extent, composition, and location at a glance. Specific images were chosen because of the predominance of one of the patterns in each of them; at the same time, they had other patterns, also showing that all pathologies could coexist in a single case of bronchiectasis, yet have a predominance of a single pattern that may have a bearing on their clinical symptoms.

Article Snippet: This study aimed to assess lung involvement in patients with bronchiectasis using the Bronchiectasis Radiologically Indexed CT Score (BRICS) and AI-based quantitative lung texture analysis software (IMBIO, Version 2.2.0).

Techniques:

Journal: Clinical Imaging

Article Title: Automated quantitative thin slice volumetric low dose CT analysis predicts disease severity in COVID-19 patients

doi: 10.1016/j.clinimag.2021.04.008

Figure Lengend Snippet: Analysis of lung texture patterns in non-severe and severe COVID-19 based on CT thorax scans. A) Radiological texture analysis per lung field was performed using the IMBIO CT Lung Texture Analysis™ software. B) Lung texture analysis shown for one patient with non-severe COVID-19 and one patient with severe disease with the percentages of normal lung parenchyma, marked in green and abnormal lung parenchyma marked in yellow for ground glass opacities and in orange for reticular pattern. Automated quantification of the lung texture in the upper, middle and lower fields with C) pictograms indicating ground glass opacity pattern localization in patients with non-severe and severe COVID-19, respectively, and D) pictograms of reticular lung texture pattern localization in patients with non-severe and severe COVID-19, respectively. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Article Snippet: Fully automated quantification of CT scans was performed via IMBIO CT Lung Texture analysis™ software.

Techniques: Software