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Medical Imaging and Pattern Recognition

Medical Imaging and Pattern Recognition. Lecture 3 Image Formats Oleh Tretiak. This Lecture. Digital Images Applications of Digital Images Image Formats General Medical. Introduction. A digital picture is a picture stored in binary (bits).

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Medical Imaging and Pattern Recognition

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  1. Medical Imaging and Pattern Recognition Lecture 3 Image Formats Oleh Tretiak MIPR Lecture 3 Copyright Oleh Tretiak, 2004

  2. This Lecture • Digital Images • Applications of Digital Images • Image Formats • General • Medical MIPR Lecture 3 Copyright Oleh Tretiak, 2004

  3. Introduction • A digital picture is a picture stored in binary (bits). • The picture resides in a digital storage system as a file. • A file is a sequence of bytes • One byte consists of 8 bits • A picture is a rectangular array of pixels MIPR Lecture 3 Copyright Oleh Tretiak, 2004

  4. Pixels, Grey Values and Quantization • Conceptually, a monochrome (black and white) image is a function f(x, y), sampled over a two-dimensional grid. • Each sample value is called a pixel (picture element). • Conceptually, the function is real-valued and has a continuous range. This is called the grey value of the pixel. • On a computer, it is represented with a finite number of bits. This is called quantization. • Most frequently, the digital quantity is interpreted as a nonnegative integer represented by a byte (8 bits). 0 ≤ v < 28 (256) MIPR Lecture 3 Copyright Oleh Tretiak, 2004

  5. Example Pixel sequence in file Raw picture format, 256x256, 1 byte per pixel [ip:KPI/Notes/Lecture 3] ojt% ls -l lena.raw -rw-r--r-- 1 ojt staff 65536 27 Sep 20:29 lena.raw [ip:KPI/Notes/Lecture 3] ojt% hexdump -x lena.raw | more 0000000 6464 6567 6466 6966 6a68 696b 6a6a 6c6b 0000010 6b6a 6764 6162 5d5a 5d5e 5d63 6b6e 7c8b MIPR Lecture 3 Copyright Oleh Tretiak, 2004

  6. Calculations • In the so-called raw format, the file contains only the gray values of the pixels. • Bits/picture = Rows x Columns x bits/pixel • Bytes/picture = Rows x Columns x bytes/pixel • Example: • For the previous slide, 256 rows, 256 columns, 1 byte per pixel. • Bytes = 256x256x1 = 65536 MIPR Lecture 3 Copyright Oleh Tretiak, 2004

  7. Examples 256x256, 4 bit, 32 kB 256x256, 1 bit, 8 kB 256x256, 4 bit, 32 kB 128x128, 4 bit, 16 kB 256x256, 2 bit, 32 kB 256x256, 8 bit, 65 kB MIPR Lecture 3 Copyright Oleh Tretiak, 2004

  8. Pixels, Quantization, and Quality • A given picture can be represented with different numbers of pixels and various numbers of bits per pixel. • Fewer pixels produces lower quality • Fewer bits per pixel produces lower quality • There is a tradeoff between quality and picture storage requirements. MIPR Lecture 3 Copyright Oleh Tretiak, 2004

  9. Uses of Digital Pictures • Photography • Medical Imaging • X-ray • CT • Ultrasound • Movies • DVD • Television MIPR Lecture 3 Copyright Oleh Tretiak, 2004

  10. Why Standard Formats? • Interoperability • Image made by Nikon, viewed on computer made by Apple. • Advantages of standards • Competition among vendors (lower prices) • Creation of markets • Multiple vendors - product cycle safety MIPR Lecture 3 Copyright Oleh Tretiak, 2004

  11. Useful Data About Photograph • Size (rows and columns) • Size of print (cm) • Size of subject (cm) • Color/BW • What color? File format should contain these data MIPR Lecture 3 Copyright Oleh Tretiak, 2004

  12. TIFF • Tagged Image File Format • Proprietary, now owned by Adobe • Many different options (easy to write, hard to read) • File contains information about • Rows and columns • How many components (colors, overlays) • Bits per channel • Example: lena.raw - 65,536 Bytes, lena.tif - 66,304 B • Extra storage (768 Bytes) used to store information about image. MIPR Lecture 3 Copyright Oleh Tretiak, 2004

  13. Image Coding (Compression) • Why compress? • Store more pictures in same memory • Spend less time sending picture over web • Lossless compression: • Decompress file and get the same picture, bit - for - bit • Typically, two-fold compression only for gray value images. • Lossy compression: • Decompress and get something similar. • Any amount of compression is possible. • Tradeoff between image quality and compression. MIPR Lecture 3 Copyright Oleh Tretiak, 2004

  14. Lossless Compression • Many ways have been developed • In practice, Lempel-Ziv (zip, gzip, etc) is the only one used. • Get 2-fold compressions over raw format • Can be included in TIFF MIPR Lecture 3 Copyright Oleh Tretiak, 2004

  15. JPEG • JPEG = joint photographic experts group, standard released in 1992. • In practice (almost) only lossy image compression scheme used in practice. • Standard has many options, only one is used in practice. MIPR Lecture 3 Copyright Oleh Tretiak, 2004

  16. Example of JPEG compression Very high quality: compression = 2.33 Photoshop Image Very low quality: compression = 115 Produced by MATLAB with Quality = 0 MIPR Lecture 3 Copyright Oleh Tretiak, 2004

  17. Block Diagram — JPEG DCT • Image is divided into 8x8 blocks • The discrete cosine transform (DCT) is computed of each block. • The transform values are encoded. MIPR Lecture 3 Copyright Oleh Tretiak, 2004

  18. JPEG DCT Decoder The values for each block are decoded. Decoded values are inversely transformed (inverse DCT), producing 8x8 pixel blocks. The blocks are assembled into a picture. MIPR Lecture 3 Copyright Oleh Tretiak, 2004

  19. JPEG Files • In practice (2004) • DCF - Design rules for the Camera File system (DCF) • Can include motion pictures, sound. • EXIF - Exchangeable image file format for digital still cameras • Data about time picture taken, focal length, etc. • File can be uncompressed (TIFF) • Compressed data in JPEG format MIPR Lecture 3 Copyright Oleh Tretiak, 2004

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  22. Medical Image Environment • Imaging devices, procedure rooms • X-ray, CT, MRI, Ultrasound, Nuclear • Patient information system • Patient history, images, scheduling/management/billing • Reliable massive storage devices. • Reading stations • Radiologists view images and history, generate reports. • All connected through network and storage MIPR Lecture 3 Copyright Oleh Tretiak, 2004

  23. DICOM Standard • Digital Imaging and Communication in Medicine • Ongoing standard activity • Sponsored by the American College of Radiology (ACR) and National Electronics Manufacturers Association (NEMA) • 22 workgroups MIPR Lecture 3 Copyright Oleh Tretiak, 2004

  24. Features of DICOM • Unit of data: Imaging Procedure • Procedure includes collection of images with specified goal, and includes specification of disease, organ, imaging device, contrast agent, etc. • The DICOM standard is object-oriented. MIPR Lecture 3 Copyright Oleh Tretiak, 2004

  25. MIPR Lecture 3 Copyright Oleh Tretiak, 2004

  26. What are “Medical Images” • The basic unit is an imaging procedure • Can consist of several images • Data can be “three dimensional” • Multiple slices, e. g. CT • Auxiliary non-image data • Patient history • Contrast agent • Date, time, ... MIPR Lecture 3 Copyright Oleh Tretiak, 2004

  27. DICOM and Other Standards • Image standards in DICOM are from other sources • TIFF, JPEG • Distinguishing features: • 12, 16 bits per pixel • Schemes for dealing with three dimensions (not covered by other standards) MIPR Lecture 3 Copyright Oleh Tretiak, 2004

  28. Ultrasound of Breast Lesion MIPR Lecture 3 Copyright Oleh Tretiak, 2004

  29. Issues • File size • Image quality • Interoperability MIPR Lecture 3 Copyright Oleh Tretiak, 2004

  30. Technology Trends: Telemedicine, PACS • Trend toward complex systems • PACS - picture archiving and communications • Critical resources • Expensive imaging devices, procedures • Medical expertise • Technological solutions • Bring patient to scanner • Bring image to expert • Digital imaging, databases, networks, standards are an essential part of the answer MIPR Lecture 3 Copyright Oleh Tretiak, 2004

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