DICOM (Digital Imaging and Communications in Medicine) is the rising, global standard for handling data like image studies. This includes the guidelines for preserving, printing and sharing imaging data in the healthcare firms. It also provides guidelines for the file format that is generally referred to as a DICOM file format and a protocol for the network communication systems being used. The protocol is an essential guideline that defines the standard IP for communication across various verticals. A DICOM medical imaging data system is comprised of several different parts, depending on what functions you need by your digital medical imaging equipment to do. Archiving or storage of digital images occurs through the use of DICOM web server. When it is used in conjunction with a DICOM web viewer, one can see the digital images that are needed for diagnosis purpose.
The DICOM compliant files can be easily shared among any unit which is capable to receive patient data, including patient scans in compliance with set standards. Many healthcare firms have implemented the use of DICOM technology to assist in the productivity of their firms, but productivity is just one advantage among many of them. DICOM medical imaging data in medical practice assist in the accurate and appropriate preservation, printing and transmission of images and files. This provides patients and doctors with faster and clean image results and the ability to post process the image. Post processing of the image allows the operator to manipulate the pixel shades to correct image density and zoom into the problem areas of the images as well as perform other procession functions that could result in improved diagnosis and fewer repeated examinations.
A method of medical image quantification data comprising up of,
• Obtaining spatial transform information representing a correspondence between pointes in a first non-transformed image and corresponding points in a second non-transformed image.
• Store the spatial transform information in a computer memory.
• Identify a first image region in the first non-transformed image.
• With one or more processors, transforming the identified first image region to identify a corresponding second image region in the second non-transformed image based on the spatial transform information...
• With the one or more processors, computing a quantification value relating to the second image region based on image values of the second non-transformed image within the second image region and image values of the first non-transformed image accessed from the first non-transformed image in accordance with the stored spatial transform.
All the computer aided diagnosis whatever is using in these days in healthcare sector are first in the market for medical image quantification. All the diagnosis methods run to provide with resulting DICOM medical imaging data as well as PDF reports or 3D representations of tissues. All these things are supported by imaging viewer. As a sector of scientific research, medical imaging constitutes a sun-discipline or biomedical engineering, medical physics on the context. Analysis and progress in the field of instrumentation, image acquisition, modeling and quantification are usually the preserve of biomedical engineering, medical physics and computer science.
Ethan Aldrin explains how cloud-based DICOM medical imaging data has revolutionized the way clinical analysis and medical intervention is carried out. He has found MedimSight cloud technologies very innovative since they include a biomarker medical image quantification system to generate top-quality data that can be viewed, stored and analyzed in just one place. https://www.medimsight.com/