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Explore the basics of medical imaging systems, including image acquisition, processing, and various medical applications.
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INFO-I530 (Foundation of Health Informatics) Medical Imaging Systems Lecture #11
Lecture in a Nutshell • Introduction • Image Acquisition Sources • Digitized Images • Basic Image Processing Principles • Sample Medical Applications • Imaging Management and Communication Systems
Introduction • Medical images include radiological images (conventional radiography or tomography), nuclear-medicine, ultrasound, photography (used in cytology, pathology, dermatology, electrofluoresence or chromosome maps), films (endoscopy), functional images obtained through reconstruction (tomodensitometry, magnetic resonance imaging), or create virtual reality. • Two broad types of images: • physical, optical, or electromagnetic (X-ray) images, which are analog and continuous by nature; • mathematical images, digital by nature, generally corresponding to matrices of numbers, which generally represent the distribution of luminous intensities on all points of the image. • Information technology can assist in all phases: • directly generates certain types of images: CAT scan, PET scan and MRI • image processing: improve image quality, identify quantitative parameters of clinical interest, propose interpretations, set up feedback loops • image compression reduces the amount of storage required and the transmission time between distant sites (e.g. teleradiology, telecytopathology).
Image Acquisition Sources • Conventional radiologyusing ionizing radiation from an X-ray source, remains the most prevalent method in radiology departments. It allows for short exposure times. Digitized images may be produced directly (digital radiology) using phosphorous plates to replace conventional films. • Digital angiography displays the underlying vessels by subtracting undesirable structures (bones and organs) from the images. Example of an image obtained by subtraction in digital angiography. The image (c) is obtained by subtracting image (a) from (b).
Image Acquisition Sources cont. • Computerized tomography also uses X-rays, but instead of being obtained directly, the image is rebuilt from the attenuation of the rays observed in different directions. • Magnetic resonance imaging (MRl) techniques reconstruct images based on hydrogen atoms resonation in a magnetic field. Without using ionizing radiation, MRI provides images that depend on the metabolism and the characteristics of the tissues through which they pass. The principle of computerized tomography
Image Acquisition Sources cont. • Ultrasounds are based on an acoustic probe that emits ultrasonic waves. The probe also captures the reflected waves, and the probe's piezoelectric crystals convert the acoustic echoes into electrical signals. • Scintigraphic imaging is performed by injecting a radioactive isotope (marker) attached to a biological component (tracer) that has an affinity for a certain organ (e.g. the thyroid or the surrenal). • Other images can be captured by video camera (endoscopy, microscopic pathological anatomy images, etc.) or from a photograph. True color processing is often necessary. • Virtual reality is based on the creation of images based on the description of objects. These objects, set in three-dimensional space, may have colors and texture, and be subjected to various conditions of lighting, orientation and motion (e.g., the force of gravity).
Image Acquisition Sources cont. Characteristics of a few radiological imaging techniques
Digitized Images • Spatial Coding Images can only be processed by computers in the form of tables of numbers. A two-dimensional table (x,y) can represent a simple, two-dimensional image. Each element in the table corresponds to an elementary square surface or pixel (picture element). A three-dimensional table (x,y,z) is required to represent a volume. Each element in the table represents an elementary cube or voxel (volume element). Pixel size defines the spatial resolution. The smaller the size, the less the digitizing process will lose information compared to the source image. Pixel sizes of less than 0,2 x 0,2 mm are necessary to maintain standard radiography quality.
Digitized Images cont. • Intensity CodingThe density of each pixel is coded on d bits. Eight-bit coding provides 256 coding levels, while 12-bit coding provides 2^12 = 4096 levels. This number determines the contrast resolution. • Temporal CodingThe temporal resolution measures the time required to create an image. A real-time application may require the creation of 30 images per second. At this speed, it is possible to obtain a clear image of an organ in movement, such as the heart. • Digitizing ImagesIn practice, digitizing systems frequently use square matrices corresponding to powers of 2 (256 x 256, 512 x 512, 1024 x 1024 pixels) with coding density from 8 to 24 bits. A two-dimensional sequence of images over time requires a three-dimensional (3-D) table (x, y, t) and a 3-D sequence of images (volumes) requires a four dimensional table (x, y, z, t). Image sequences recorded over time may be coupled with physiological signals such as ECG.
Digitized Images cont. The principle of digitizing images. (a) is the original image. Selecting the sampling window leads to the matrix (b) obtained by quantifying on a scale of 10 gray levels (0=white, 9 =black)
Basic Image Processing Principles • The preprocessing phase improves image quality, and the segmentation phase isolates the elements that make up the image. Beyond these steps, we enter the realm of high-level vision. This involves extracting significant parameters of the image (e.g., the volume of a tumor or the degree of a stenosis) which playa role in its interpretation. The interpretation phase may lead to a diagnosis, a prognosis, or even a procedure as in robotics. The imaging process
Basic Image Processing Principles cont. • Image PreprocessingThe preprocessing phases eliminate imperfections related to the image generation system and reduce noise. The techniques used normally transform the value of each pixel in the original image into a new value obtained by a mathematical function. • Noise Reduction: Different filtering techniques can reduce this noise. The smoothing method recalculates the density of each point according to the density of the adjacent points. • Modifying Image Contrast: Calculating the histogram of an image creates a re presentation of the number of pixels for each gray level (density) of the image. Analysis of the histogram makes apparent the distribution of gray levels and helps judge the quality of the digitization. If the histogram is centered on density values that are too weak or too strong. Operations to transform the histogram of an image may improve the contrast (and the visual perception) in particular gray areas. • Geometric Operations on Images: perform block moves on an image and generate an unvarying output image after a translation or a rotational movement.
Basic Image Processing Principles cont. • SegmentationThe segmentation phase isolates elements in the image (organs, vessels, microscopic cells, etc.). The methods are usually based on identifying differences in density around the edges of the desired object. The threshold method keeps only pixels whose intensity is between upper and lower limits. The outline isolation method plots the levels of a digitized image to show the structure and the shape of the organ. Isolated outlines of a thyroid gland
Basic Image Processing Principles cont. • Extracting ParametersThis technique can be used when measuring a surface or a volume (e.g., cardiac volume, the volume of a tumor), quantifying shrinkage (e.g., vascularstenosis), evaluating a texture (e.g., bone density) or counting elements (e.g., cells or calcifications). • Image InterpretationAutomatic computer interpretation of images presents complex research problems. It requires knowledge of several disciplines, in particular anatomy and pathological anatomy. The structures and parameters identified must be compared to known structures and then classified. A combination of images obtained using different image capturing methods or clinical or biological data is often required to propose an automatic diagnosis.
Sample Medical Applications • Quantifying the Degree of a Vascular StenosisTreatment of vascular stenosis was revolutionized by endoluminal dilation techniques, which avoided complex surgery. Therapeutic indication and remote patient care require a precise quantification of the arterial lesions, which may be performed automatically or semi-automatically. Automatic stenosis detection and quantification in a renal arteriography
Sample Medical Applications cont. • Identifying ChromosomesIdentification of chromosomes when determining the karyotype uses pattern recognition techniques. The 23 pairs of human chromosomes may be identified by their relative size and the position of their centromere.The image of a cytological preparation is digitized, and its variations in density are analyzed. After identifying each chromosome, the computer tries to group them in pairs. Analysis of chromosomes, determination of the profile
Sample Medical Applications cont. • Computer-Aided Surgical TechniquesThe objective of computer-aided surgery is to facilitate certain surgical techniques. The techniques used are part of the classical robotics loop: perception reasoning-action. The perception step concerns the acquisition of the necessary images, often using several methods. Computer-aided surgical gesture
Imaging Management and Communication Systems • Tele-expertiseExchanging information requires a high degree of interactivity and may necessitate access to information already stored in patient records. The techniques used include the transmission of voice, digitized images, and also video techniques and videoconferencing, eventually integrated in a single workstation. • PACSThe PACS (picture archiving and communication system) is designed to: (1) store digital images without the risk of loss or deterioration of their contents; (2) provide quick and easy access to all images for all authorized individuals; (3) enable local processing (for both image production centers and users).The transmission of images and related information (e.g., type of film or incidence) requires the selection of compression and communication standards such as the ACR/NEMA DICOM standard. Therefore HL7 only handles the textual data not imaging information. Images are managed by PACS and transmitted on DICOM standard.
Summary • Introduction • Image Acquisition Sources • Digitized Images • Basic Image Processing Principles • Sample Medical Applications • Imaging Management and Communication Systems