 Lossless › Integer wavelet (+/- reversible color transformation).  Either lossless or lossy › Integer or floating point wavelet  Many features! › Region-of-interest.

Slides:



Advertisements
Similar presentations
Digital Color 24-bit Color Indexed Color Image file compression
Advertisements

The Binary Numbering Systems
What is DICOM? The standard for Digital Imaging and Communications in Medicine. Developed by the National Electrical Manufacturers Association (NEMA) in.
Mpeg-21 and Medical data A strategy for Tomorrow ’ s EMR.
Chapter 2 Digital data Ola A. Younis. Elements of digital media Symbols : representation for something else. Example: a group of letters often serve as.
School of Computing Science Simon Fraser University
School of Engineering and Computer Science Victoria University of Wellington Copyright: Peter Andreae & david streader, VUW Images and 2D Graphics COMP.
Fractal Image Compression
Graphics File Formats. 2 Graphics Data n Vector data –Lines –Polygons –Curves n Bitmap data –Array of pixels –Numerical values corresponding to gray-
A 24-bit depth.bmp file made in XVI32 This 2-by-2 image was handcrafted in XVI32 Bytes 1C-1D hex in the Info Header say that the image uses 24-bit (18.
CS430 © 2006 Ray S. Babcock Lossy Compression Examples JPEG MPEG JPEG MPEG.
1 A Balanced Introduction to Computer Science, 2/E David Reed, Creighton University ©2008 Pearson Prentice Hall ISBN Chapter 12 Data.
5. 1 JPEG “ JPEG ” is Joint Photographic Experts Group. compresses pictures which don't have sharp changes e.g. landscape pictures. May lose some of the.
Roger Cheng (JPEG slides courtesy of Brian Bailey) Spring 2007
TUMChair for Computer Aided Medical Procedures (I-16)1 Intra-operative Imaging & Visualization Lab Course SS 2004 Lab Course SS 2004 Implementation of.
DICOM Conformance Statement (DCS) A Proven Power within DICOM
The Medicine Behind the Image DICOM Compression 2002 David Clunie Director of Technical Operations Princeton Radiology Pharmaceutical Research.
Image and Sound Editing Raed S. Rasheed Image Image. Digital image. – Raster images. – Vector Images. – Stereo Images. – Image File Formats Lossless.
An Introduction to Scanning and Storing Photographs and Graphics Bryn Jones Aug 2002
Data starts with width and height of image Then an array of pixel values (colors) The number of elements in this array is width times height Colors can.
Digital Images The digital representation of visual information.
Department of Physics and Astronomy DIGITAL IMAGE PROCESSING
Graphic images for computers Stored in files of binary data - Binary blobs Software has to know the binary format to decode the file and render an image.
Graphics/Image Data Types
1 Perception, Illusion and VR HNRS 299, Spring 2008 Lecture 14 Introduction to Computer Graphics.
Lecture 5. Topics Sec 1.4 Representing Information as Bit Patterns Representing Text Representing Text Representing Numeric Values Representing Numeric.
Digital Cameras And Digital Information. How a Camera works Light passes through the lens Shutter opens for an instant Film is exposed to light Film is.
JPEG. The JPEG Standard JPEG is an image compression standard which was accepted as an international standard in  Developed by the Joint Photographic.
Archival and Communication of DICOM Images on a Hospital Network Sheikh Mahmood H.M School of Biomedical Engineering IIT - Bombay.
Computer Images Can store color info about each pixel, but makes file BIG Compression for Web 15.
Image Representation. Digital Cameras Scanned Film & Photographs Digitized TV Signals Computer Graphics Radar & Sonar Medical Imaging Devices (X-Ray,
Marr CollegeHigher ComputingSlide 1 Higher Computing: COMPUTER SYSTEMS Part 1: Data Representation – 6 hours.
Computer Science 1 Week 10.
Multimedia Basics (1) Hongli Luo CEIT, IPFW. Topics r Image data type r Color Model : m RGB, CMY, CMYK, YUV, YIQ, YCbCr r Analog Video – NTSC, PAL r Digital.
DICOM INTERNATIONAL DICOM INTERNATIONAL CONFERENCE & SEMINAR April 8-10, 2008 Chengdu, China Exchanging Imaging Data Herman Oosterwijk Add logo if desired.
Digital Images are represented by manipulating this…
CS 325 Introduction to Computer Graphics 04 / 12 / 2010 Instructor: Michael Eckmann.
 By Bob “The Bird” Fiske & Anita “The Snail” Cost.
Image File Formats. What is an Image File Format? Image file formats are standard way of organizing and storing of image files. Image files are composed.
Exchanging Imaging Data
Image File Formats By Dr. Rajeev Srivastava 1. Image File Formats Header and Image data. A typical image file format contains two fields namely Dr. Rajeev.
WEB GRAPHICS EXPLORING COMPUTER SCIENCE - LESSON 3-4.
Graphics and Image Data Representations 1. Q1 How images are represented in a computer system? 2.
IS502:M ULTIMEDIA D ESIGN FOR I NFORMATION S YSTEM M ULTIMEDIA OF D ATA C OMPRESSION Presenter Name: Mahmood A.Moneim Supervised By: Prof. Hesham A.Hefny.
Submitted To-: Submitted By-: Mrs.Sushma Rani (HOD) Aashish Kr. Goyal (IT-7th) Deepak Soni (IT-8 th )
September, 2005What IHE Delivers 1 Stefan Claesen – Medflow Inc In partnership with Visbion Ltd IHE Eye Care Webinar Requirements for PACS\IMS vendors.
The DICOM Standard Miloš Šrámek Austrian Academy of Sciences.
8th Lecture – Intro to Bitmap or Raster Images
Exploring Computer Science - Lesson 3-4
Graphics and image data representation
Images and 2D Graphics COMP
Sampling, Quantization, Color Models & Indexed Color
Exploring Computer Science - Lesson 3-4
Chapter 3 Graphics and Image Data Representations
JPEG.
A Closer Look at Instruction Set Architectures
Exploring Computer Science - Lesson 3-4
"Digital Media Primer" Yue-Ling Wong, Copyright (c)2013 by Pearson Education, Inc. All rights reserved.
Chapter III, Desktop Imaging Systems and Issues: Lesson IV Working With Images
Image File Size and File Compression
Ultrasound Image Encoding
6th Lecture – Rectangles and Regions, and intro to Bitmap Images
Data Representation.
Representing Images 2.6 – Data Representation.
COMS 161 Introduction to Computing
Image Coding and Compression
Real-World File Structures
Chapter 8 – Compression Aims: Outline the objectives of compression.
Presentation transcript:

 Lossless › Integer wavelet (+/- reversible color transformation).  Either lossless or lossy › Integer or floating point wavelet  Many features! › Region-of-interest coding. Fewer bits for background › Progressive by contrast. › Transform in 3rd. Dimension!.

 Part 10 describes a format for files  Extension.dicom, dcm.  File composition › Header (info about patient name, type of scan, image dimension etc) › Image data  Files can be compressed using lossy or lossless variant of JPEG

 the first 794 bytes are used for a DICOM format header. Describes image dimensions and retains other text information about the scan  The image data follows the header information (the header and the image data are stored in the same file)  DICOM requires a 128-byte preamble (these 128 bytes are usually all set to zero), followed by the letters 'D', 'I', 'C', 'M'

 This is followed by the header information, which is organized in 'groups‘ the group 0002hex is the file meta information group, and (in the example on the left) contains 3 elements: one defines the group length, one stores the file version and the third stores the transfer syntax.

 The DICOM elements required depends on the image type, and are listed in Part 3 of the DICOM standard. For example, this image modality is 'MR' (see group:element 0008:0060), so it should have elements to describe the MRI echo time  Of particular importance is group:element 0002:0010. This defines the ' Transfer Syntax Unique Identification ' (see the table on the left). This value reports the structure of the image data, revealing whether the data has been compressed  the Transfer Syntax UID also reports the byte order for raw data. Different computers store integer values differently, so called 'big endian' and 'little endian' ordering. Consider a 16- bit integer with the value 257: the most significant byte stores the value 01 (=255), while the least significant byte stores the value 02. Some computers would save this value as 01:02, while others will store it as 02:01. Therefore, for data with more than 8-bits per sample, a DICOM viewer may need to swap the byte-order of the data to match the ordering used by your computer

 In addition to the Transfer Syntax UID, the image is also specified by the Samples Per Pixel (0028:0002), Photometric Interpretation (0028:0004), the Bits Allocated (0028:0100). For most MRI and CT images, the photometric interpretation is a continuous monochrome (e.g. typically depicted with pixels in grayscale). In DICOM, these monochrome images are given a photometric interpretation of 'MONOCHROME1' (low values=bright, high values=dim) or 'MONOCHROME2' (low values=dark, high values=bright). However, many ultrasound images and medical photographs include color, and these are described by different photometric interpretations (e.g. Palette, RGB, CMYK, YBR, etc)

This is simply a way of describing the 'brightness' and 'contrast' of the image. These values are particularly important for Xray/CT/PET scanners that tend to generate consistently calibrated intensities so you can use a specific C:W pair for every image you see (e.g. 400:2000 might be good for visualising bone, while 50:350 might be a better choice for soft tissue). A good starting estimate for this image might be a center of 85 (mean intensity) and width of 171 (range of values), as shown in the middle panel. Reducing the width to 71 would increase the contrast (left panel). On the other hand, keeping a width of 171 but reducing the center to 40 would make the whole image appear brighter

 Complex services are built using service elements, called DICOM message service elements, or DIMSEs.  There are both composite and normalized services for composite and normalized information objects.  There are 5 DIMSEs that are used for composite information objects (called DIMSE-C) and 6 that are used for normalized information objects (called DIMSE-N).  Two categories of DIMSEs: › operations (such as "store") › notifications (such as "event report”)

 DIMSE-C services: › Operations:  C-Store  C-Get  C-Move  C-Find  C-Echo › No notification services

 The C-STORE service is invoked by a DIMSE-service-user to request the storage of Composite SOP Instance information by a DIMSE-service-user.  The C-FIND service is invoked by a DIMSE-service-user to match a series of Attribute strings against the Attributes of the set of SOP Instances managed by a DIMSE-service-user. The C-FIND service returns for each match a list of requested Attributes and their values.  The C-GET service is invoked by a DIMSE-service-user to fetch the information for one or more information objects from a DIMSE-service-user, based upon the Attributes supplied by the invoking DIMSE-service-user.

 The C-MOVE service is invoked by a DIMSE- service-user to move the information for one or more Composite SOP Instances from a DIMSE- service-user, to a third party DIMSE-service-user, based upon the Attributes supplied by the invoking DIMSE-service-user.  The C-ECHO service is invoked by a DIMSE- service-user to verify end-to-end communications with a DIMSE-service-user.