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ABSTRACT
A unique synthesis of scientific content and artistic style, Biomedical Imaging, Analysis provides a comprehensive overview of the advances spurring the evolution of imaging science practice.The focus of Biomedical Imaging is on comprehensive explanation and ample illustration, rather than complex physics or mathematics. A brief review of fundamental principles and underlying theories precedes detailed discussions of innovative imaging methods, novel visualization techniques, new processing algorithms, image modeling, and biomedical applications useful in medical training. Embracing CT and MR Elastography, parametric displays, volumetric modeling algorithms, surgical and radiation treatment planning, image-guided diagnosis and treatment, virtual endoscopy, epilepsy imaging, and cardiac motion analysis. The success of implementing these novel agendas and concepts will have tremendous impact to better present and future healthcare delivery.

KEYWORDS: Imaging, Efficient, Analysis, Methodology, Enhancement, Explanation

INTRODUCTION
Image (from Latin word ‘imago’), is an artifact like a two dimensional picture, that has a similar appearance to some subject like a physical object or a person. Image processing is any form of signal processing for which the input is an image and the output may either be an image or a set of characteristics or parameters related to the image. Image processing is used in areas such as multimedia, computing, secured image communication, biomedical imaging, remote sensing, pattern recognition, image compression and retrieval, etc.

Biomedical Imaging
It is the technique and process used to create images of the human body or parts of it for clinical purposes or for studying anatomy and physiology. A multitude of diagnostic medical imaging systems are used to probe the human body. They comprise both microscopic (viz. cellular level) and macroscopic (viz. organ and systems level) modalities. Biomedical image processing includes the analysis, enhancement and display of images captured via instruments such as X-Ray, Ultrasound, MRI (Magnetic Resonance Imaging),CT scanners, nuclear medicine and optical imaging technologies.

Figure SEQ Figure * ARABIC 1: bio-medical image of brain
METHODOLOGY
Need of image processing in medicine
Main tasks performed by the image processing unit in medicine are:
Interfacing analog outputs of sensors such as microscopes, endoscopes, ultrasound etc., to digitizers and in turn to Image Processing systems.

Image enhancements.

Changing density dynamic range of B/W images.

Color correction and manipulating of colors within a color image.

Contour detection and area calculations of the cells of a biomedical image.

Restoration and smoothing of images.

Registration of multiple images and creating mosaic of multiple images.

Construction of 3-D images from 2-D images.

Generation of negative images.

Zooming of images.

Removal of artifacts from the image.

Principles of image processing
An image is usually a function of two spatial variables, e.g. fx, y, which represents the brightness f at the Cartesian location x, y.

It can also be defined as an array, or a matrix, of square pixels (picture elements) arranged in columns and rows.

After converting image information into an array of integers, the image can be manipulated, processed, and displayed by computer.

Computer processing is used for image enhancement, restoration, segmentation, description, recognition, coding, reconstruction, transformation.

Types of Images
1. Analog image
An analog image is described by the spatial distribution of brightness or gray levels that reflect a distribution of detected energy.

The image can be displayed using a medium such as paper or film.

Black and white images require only one gray level or intensity variable while color images require multiple variable like the three basic colors red, blue, green(RGB).

When combined together, the RGB intensities can produce a selected color at a spatial location of the image.

2. Digital image
A digital image is discrete in both spatial and intensity (gray level) domains.

A discrete spatial location of finite size with a discrete gray-level value is called a pixel.
For example, an image of 1024 x 1024 pixels may be displayed in 8-bit gray-level resolution. This means that each pixel in the image may have any value from 0 to 255 (i.e. total of 256 gray levels).

The pixel dimensions would depend on the spatial sampling.

Components of Image Processing
Image Formation
Image formation includes all the steps from capturing the image to forming a digital image matrix. The main steps are:
Acquisition: It is defined as the action of retrieving an image from some source, usually a hardware-based source (For example: a CT scanner).Performing image acquisition is the first step in the workflow sequence because, without an image, no processing is possible. The image that is acquired is completely unprocessed and is the result of whatever hardware was used to generate it. Acquisition methods vary for different medical instruments.

Digitization: It is the process of converting information into a digital format .In this format, information is organized into discrete units of data (called bits) that can be separately addressed (usually in multiple-bit groups called bytes). This is the binary data that computers and many devices with computing capacity can process. Different analog to digital convertors are used for converting the acquired data from instruments to digital format. The type of convertor used depends upon the required resolution, speed, application and cost. Some commonly available convertors are:
Dual Slope ADC
Successive Approximation ADC
Flash ADC
Serial or ripple ADC
Sigma Delta Convertor Type ADC
Combination of flash and successive approximation type ADC
There is a need to digitize the acquired analog data so that it can be processed with the help of different software such as MATLAB, etc.

Biomedical image processing covers biomedical signal gathering, image forming, picture processing, and image display to medical diagnosis based on features extracted from images. Some basic image processing techniques include outlining, de-blurring, noise cleaning, filtering, search and texture analysis. Image processing covers four main areas:
Image formation.

Visualization.

Analysis of image.

Management of the acquired information.

Image Enhancement and Visualization
It refers to all types of manipulation that is done on the data acquired in digital format, finally resulting in an optimized output of the image.

The purpose of image enhancement methods is to process an acquired image for better contrast and visibility of features of interest for visual examination as well as subsequent computer-aided analysis and diagnosis.

There is no unique general theory or method for processing all kinds of medical images for feature enhancement. Specific medical imaging applications (such as cardiac, neurological, muscular, mammography, etc.) present different challenges in image processing for feature enhancement and analysis. Medical images show characteristic information about the physiological properties of the structures and tissues. However, the quality and visibility of information depends on the imaging modality and the response functions of the imaging scanner. Hence the goal of this step is to:
Eliminate the extraneous components such as noise from the signal. Often this is done using linear filters. Types of filters used are: High pass Filters, Low pass Filters and Notch pass filters.

Adjust the different parameters of the image such as brightness, contrast, visibility, color saturation, etc.

Image enhancement can be accomplished using Adobe Photoshop, Corel PHOTO-PAINT and Origin software in order to achieve good quality images for accurate quantitative analysis.

Image Analysis
Image analysis includes all the steps of processing, which are used for quantitative measurement as well as interpretation of biomedical images.

These steps require a prior knowledge of the nature and content of the images, which is integrated into the algorithm on a high level of abstraction.

Thus the process of image analysis is very specific, and developed algorithms can be transferred directly to application domains.

Image Management
Image management sums up all the techniques that provide the efficient storage, communication, transmission, archiving, and access (retrieval) of image data.

The methods of telemedicine are also a part of image management. There are different formats in which the digital image can be stored in memory. Some of the most common file formats used for saving images in the digital form (in hard drive or memory) is:
GIF: An 8-bit (256 color), non-destructively compressed bitmap format. Mostly used for web. It has several sub-standards one of which is the animated GIF.

JPEG: It is a very efficient (i.e. much information per byte) destructively compressed 24 bit (16 million colors) bitmap format.

TIFF: It is the standard 24 bit publication bitmap format.

Image compression is also a part of image management. Through image compression large no. of images can be stored and made available to many places at the same time through appropriate communication networks and protocols such as the Digital Imaging and Communications in Medicine (DICOM) protocol.

Types of Biomedical Imaging Process:
X-RAY MACHINE AND DIGITAL RADIOGRAPHY
Two-dimensional projection radiography is the oldest medical imaging modality and is still one of the most widely used imaging methods in diagnostics.

Conventional film radiography uses an X-Ray tube to focus a beam on the imaging area of a patient’s body to record an image on a film. The image recorded on the film is a 2-D projection of the three-dimensional (3-D) anatomical structure of the human body.

Scattering can create a major problem in projection radiography. The scattered photons can create artifacts and artificial structures in the image that can lead to an incorrect interpretation or at least create a difficult situation for diagnosis.

In case of digital radiography, the combination of intensifying screen and film is replaced by a phosphor layered screen coupled with a charge-coupled device (CCD)-based panel. A solid-state detector system in digital radiography uses a structured thallium-doped cesium iodide (CsI) scintillation material to convert X-Ray photons into light photon, which are then converted into electrical signal by CCDs through a fiber optics coupling interface.

Electrical output signal sensitivity can be controlled much more efficiently than in a film-based system. The digital detector system also provides excellent linearity and gain control, which directly affects the SNR of the acquired data. For this reason, a digital detection system provides a superior dynamic range compared with the film-based systems.

Figure SEQ Figure * ARABIC 2: digital x ray machine

Figure SEQ Figure * ARABIC 3:x-ray of spine and lower limbs
MAGNETIC RESONANCE IMAGING SYSTEM
Magnetic resonance imaging (MRI) is a noninvasive medical test that helps physicians diagnose and treat medical conditions. MRI uses a powerful magnetic field, radio frequency pulses and a computer to produce detailed pictures of organs, soft tissues, bone and virtually all other internal body structures.

The hydrogen proton is the most common form of nuclei used in MRI. The three properties of hydrogen nuclei (protons) mapping are the spin-lattice relaxation time Ti, Spin-spin relaxation time T 2, and the spin density p.

Magnetic resonance imaging is a complex multidimensional imaging modality that produces extensive amounts of data. Imaging methods and techniques applied in signal acquisition allow reconstruction of images with multiple parameters that represent various physical and chemical properties of the matter of the object.

The imager system includes the computer for image processing, display system and the control console. The computer system collects the signal after analog to digital conversion, corrects, recomposes and stores the image.

Analog to digital convertors of 16 bits or higher are used and during data acquisition, information is acquired at the rate of about 800kbps.

Algorithms like the fast Fourier transformation is used to convert the time domain data to image data. Data is stored on high speed disks.

Figure SEQ Figure * ARABIC 4: major components of mri system
X-RAY COMPUTED TOMOGRAPHY (CAT SCAN)
It uses computer-processed X-rays to produce images of specific areas of a scanned object, allowing the user to see inside the object without cutting.

Digital geometry processing is used to generate a 3-D image of the inside of the object from a large series of two-dimensional radiographic images taken around a single axis of rotation. The cross-sectional images are used for diagnostic and therapeutic purposes in various medical disciplines. CT produces a volume of data that can be manipulated in order to demonstrate various bodily structures based on their ability to block the X-ray beam.

In conventional CT machines, an X-ray tube and detector are physically rotated behind a circular shroud. Sometimes contrast materials such as intravenous iodinated contrast are used. This is useful to highlight structures such as blood vessels that otherwise would be difficult to delineate from their surroundings. Using contrast material can also help to obtain functional information about tissues.

A visual representation of the raw data obtained is called a sinogram, yet it is not sufficient for interpretation. Once the scan data has been acquired, the data must be processed using a form of tomographic reconstruction, which produces a series of cross-sectional images.

In terms of mathematics, the raw data acquired by the scanner consists of multiple “projections” of the object being scanned. The technique of filter backed projection is one of the most established algorithmic techniques for this problem. It is conceptually simple, tunable and deterministic.

Figure SEQ Figure * ARABIC 5: cat scan of brain
ULTRASONIC IMAGING SYSTEMS
In this method a piezoelectric crystal-based transducer can be used as a source to form an ultrasound beam as well as a detector to receive the returned signal from the tissue. In a plastic casing, a piezoelectric crystal is used along with a damping material layer and acoustic insulation layer inside the plastic casing. An electromagnetic tuning coil is used to apply a controlled voltage pulse to produce ultrasound waves. In the receiver mode, the pressure wave of the returning ultrasound signal is used to create an electric signal through the tuned electromagnetic coil.

The total travel distance traveled by the ultrasound pulse at the time of return to the transducer is twice the depth of the tissue boundary from the transducer. Thus, the maximum range of the echo formation can be determined by the speed of sound in the tissue multiplied by half of the pulse-repetition period.

When the echoes are received by the transducer crystal, their intensity is converted into a voltage signal that generates the raw data for imaging.

The voltage signal then can be digitized and processed according to the need to display on a computer monitor as an image.

Ultrasound images appear noisy with speckles, lacking a continuous boundary definition of the object structure. The interpretation and quantification of the object structure in ultrasound images is more challenging than in X-ray computed tomography (X-ray CT) or magnetic resonance (MR) images.

The operator in ultrasound imaging has a great ability to control the imaging parameters in real time.

Figure SEQ Figure * ARABIC 6: ultra sound image of twin babies
ANGIOGRAPHY
Angiography or arteriography is a medical imaging technique used to visualize the inside, or lumen, of blood vessels and organs of the body, with particular interest in the arteries, veins, and the heart chambers. This is traditionally done by injecting a radio-opaque contrast agent into the blood vessel and imaging using X-ray based techniques such as fluoroscopy.

The word itself comes from the Greek words angeion, “vessel”, and graphein, “to write” or “record”. The film or image of the blood vessels is called an angiograph, or more commonly an angiogram. Though the word can describe both an arteriogram and a venogram, in everyday usage the terms angiogram and arteriogram are often used synonymously, whereas the term venogram is used more precisely.1The term angiography has been applied to radionuclide angiography and newer vascular imaging techniques such as CT angiography and MR angiography.2 The term isotope angiography has also been used, although this more correctly is referred to as isotope perfusion scanning.

Figure SEQ Figure * ARABIC 7: angiography of fingers

MAMMOGRAPHY
A mammogram is an x-ray picture of the breast. It can be used to check for breast cancer in women who have no signs or symptoms of the disease. It can also be used if you have a lump or other sign of breast cancer.

Screening mammography is the type of mammogram that checks you when you have no symptoms. It can help reduce the number of deaths from breast cancer among women ages 40 to 70. But it can also have drawbacks. Mammograms can sometimes find something that looks abnormal but isn’t cancer. This leads to further testing and can cause you anxiety. Sometimes mammograms can miss cancer when it is there. It also exposes you to radiation. You should talk to your doctor about the benefits and drawbacks of mammograms. Together, you can decide when to start and how often to have a mammogram.

Mammograms are also recommended for younger women who have symptoms of breast cancer or who have a high risk of the disease. When you have a mammogram, you stand in front of an x-ray machine. The person who takes the x-rays places your breast between two plastic plates. The plates press your breast and make it flat. This may be uncomfortable, but it helps get a clear picture. You should get a written report of your mammogram results within 30 days.

Figure SEQ Figure * ARABIC 8: mammogram of breast
FLUOROSCOPY 
It is an imaging technique that uses X-rays to obtain real-time moving images of the interior of an object. In its primary application of medical imaging, a fluoroscope  allows a physician to see the internal structure and function of a patient, so that the pumping action of the heart or the motion of swallowing, for example, can be watched. This is useful for both diagnosis and therapy and occurs in general radiology, interventional radiology, and image-guided surgery. In its simplest form, a fluoroscope consists of an X-ray source and a fluorescent screen, between which a patient is placed. However, since the 1950s most fluoroscopes have included X-ray image intensifiers and cameras as well, to improve the image’s visibility and make it available on a remote display screen. For many decades fluoroscopy tended to produce live pictures that were not recorded, but since the 1960s, as technology improved, recording and playback became the norm.

Fluoroscopy is similar to radiography and X-ray computed tomography (X-ray CT) in that it generates images using X-rays. The original difference was that radiography fixed still images on film whereas fluoroscopy provided live moving pictures that were not stored. However, today radiography, CT, and fluoroscopy are all digital imaging modes with image analysis software and data storage and retrieval.

Figure SEQ Figure * ARABIC 9: animal fluoroscopy

CONCLUSION
In medical sciences, image processing has enabled for accurate and fast quantitative analysis and visualization of medical images of numerous modalities such as MRI, CT, X-Ray, fluoroscopy etc.

It has also enabled doctors and researchers at remote sites to easily share data and analyze, thereby enhancing their ability to diagnose, monitor and treat various medical disorders.

Due to advancement in image processing tools, it has become possible to acquire high quality images of different parts of the human body and analyze the images using various software’s, thereby facilitating the early detection of many diseases such as cancer, abnormalities in organs, etc. thus enabling accurate diagnosis which has helped in saving human life.

REFERENCESBiomedical Image Processing, Thomas Martin Deserno, Springer
Medical Image Processing, K.M.M Rao and V.D.P Rao
Medical Image Analysis, Second edition, Atam P. Dhawan, IEEE Press Series in
Biomedical Engineering
Image Processing And Data Analysis In Computed Tomography, E. D. Seleþchi1, O.

Duliu, University Of Bucharest, Romania
Handbook of Biomedical Instrumentation, Second Edition, R S Khandpur, Tata McGraw-Hill Education

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