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Related Concept Videos

Computed Tomography01:10

Computed Tomography

Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...

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Related Experiment Video

Updated: May 22, 2026

Voxel Printing Anatomy: Design and Fabrication of Realistic, Presurgical Planning Models through Bitmap Printing
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Voxel Printing Anatomy: Design and Fabrication of Realistic, Presurgical Planning Models through Bitmap Printing

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Texture-based medical image compression.

Vinayak K Bairagi1, Ashok M Sapkal, Ankita Tapaswi

  • 1Department of Electronics and Telecommunication, Sinhgad Academy of Engineering, Kondhwa (Bk.), Pune 48, India. vbairagi@yahoo.co.in

Journal of Digital Imaging
|May 3, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces a novel image compression algorithm for the medical industry. It prioritizes visual quality over pixel fidelity for efficient telemedicine data transmission.

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Last Updated: May 22, 2026

Voxel Printing Anatomy: Design and Fabrication of Realistic, Presurgical Planning Models through Bitmap Printing
11:36

Voxel Printing Anatomy: Design and Fabrication of Realistic, Presurgical Planning Models through Bitmap Printing

Published on: February 9, 2022

Area of Science:

  • Medical Informatics
  • Image Processing
  • Computer Vision

Background:

  • The internet's exponential growth in image data presents challenges for storage and transmission.
  • The medical industry faces issues with managing large volumes of patient records.
  • Automation and telemedicine necessitate efficient methods for medical data sharing.

Purpose of the Study:

  • To develop an image compression algorithm tailored for the medical industry.
  • To address the need for efficient transmission of large medical image datasets in telemedicine.
  • To prioritize visual quality for diagnostic purposes over strict pixel-wise accuracy.

Main Methods:

  • Developed a novel image compression algorithm.
  • The algorithm focuses on visual quality metrics.
  • Utilizes image edge and texture parameters for compression.

Main Results:

  • The algorithm offers a visual quality approach to image compression.
  • It effectively compresses large image datasets.
  • Suitable for transmitting medical data in telemedicine scenarios.

Conclusions:

  • The proposed algorithm provides an effective solution for medical image compression.
  • It supports efficient data transmission in telemedicine.
  • Visual quality-based compression is a viable approach for medical applications.