Apr 7, 2020 · Understanding porcine cardiac dimensions through three-dimensional computed tomography (CT), increases preclinical study success, leading to higher cost efficiency and to the observance...

Jun 1, 2022 · To explore the respiratory and circulatory system in pigs, a deep learning based computational pipeline was built to extract the size of lungs and hearts from CT-scan images. This pipeline was...

May 4, 2022 · While a “blind” lumbar puncture (LP) can sample cerebrospinal fluid (CSF), it is unreliable for drug delivery in pigs. Using computed tomography (CT) we determined the underlying anatomical reasons. The pig spinal cord was visualized terminating at the S2-S3 level.

This study aims to describe the anatomic features of the porcine using computerized tomography (CT) scan. Methods: Thirty large, white, female pigs were included in this study. The CT image acquisition was performed in four-phase contrast study.

Feb 1, 2019 · The model is developed from data points digitized from a 3D pig CT image. In total 84 muscles and 121 bones are included in the atlas, representing the tissue structures most relevant to the industry.

In this communication we present a novel pig atlas model which is represented by a parametric linear Lagrange or cubic Hermite mesh. The model is developed from data points digitized from a 3D pig CT image.

Jan 1, 2019 · A high-resolution computed tomographic (CT) whole-animal post-mortem scan of one pig was also performed to verify the large sample CT capabilities of the IMBL.

To explore the respiratory and circulatory system in pigs, a deep learning based computational pipeline was built to extract the size of lungs and hearts from CT‐scan images. This pipeline was...

Apr 1, 2021 · In this paper, a noninvasive method for CT segmentation is proposed, to automatically quantify pig composition and calculate the proportion of fat, lean meat, and bone, with the assistance of deep neural networks.

Aug 1, 2017 · Removal of internal organs such as lungs, liver, and kidneys is a key step required to compute the lean meat percentage from Computed Tomography (CT) scans of live animals. In this paper, we propose two segmentation techniques to remove these organs focusing on pigs.