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Computer Aided Diagnosis
Computer Aided Diagnosis
Personally, I found Computer Aided Design (CAD) to be a very interesting health technology. CAD is normally performed by a radiologist. CAD are procedures in medicine that assist doctors in the interpretation of medical images. CAD is also know as Computer Aided Diagnosis and are procedures that assist doctors in the interpretation of medical images. Imaging techniques in X-Ray, MRI, and Ultrasound diagnostics yield a great deal of information, which the radiologist has to analyze and evaluate comprehensively in a short time. CAD systems help scan digital images,
from computed tomography, for typical appearances and to highlight conspicuous sections, such as possible diseases.
CAD is a very young interdisciplinary technology combining elements of artificial intelligence and digital image processing with radiological imaging processing. A typical application is the detection of a tumor. For instance, some doctors use CAD to support preventive medicine check-ups in mammography (diagnosis of breast cancer), the detection of polpys in the colon, and lung cancer.
CAD is used in the diagnosis of breast cancer, lung cancer, colon cancer, prostate cancer, bone mestastases, and coronary artery disease. In my opinion, these applications are very critical in the identification of various forms of legions and tumors etc. These are very huge applications because most of those diagnosis can lead to death. Early detection increases the chance of saving lives.
CAD is used in screening mammography (X-ray examination of the female breast). Screening mammography is used for early detection of breast cancer. CAD is especially established in US and the Netherlands and is used in addition to human evaluation, usually by a radiologist. Some studies suggest a positive impact on mammography screening programs, but others show no improvement. A 2008 systematic review on computer aided detection in screening mammography concluded that CAD does not have a significant effect on cancer detection rate, but does undesirably increase recall rate (i.e. the rate of false positives).
This is another testament to the potential of CAD. As we all know, cancer is the second leading cause of death among women so as this technology improves over-time, it will only enhance the detection rate of breast cancer. Obviously, based on the current statistics, it still has a lot of room to improve.
In the diagnosis of lung cancer, computed tomography with special three-dimensional CAD systems are established and considered as gold standard. At this a volumetric dataset with up to 3.000 single images is perpared and analyzed. Round lesions (lung cancer, metastases and benign changes) from 1 mm are detectable. Today all well-known vendors of medical systems offer corresponding solutions. Early detection of lung cancer is valuable. The 5-year survival-rate of lung cancer has stagnated in the last 30 years and is now at approximately just 15%. Lung cancer takes more victims than breast cancer, prostate cancer and colon cancer together. This is due to the asymptomatic growth of this cancer. In the majority of cases it is too late for a successful therapy if the patient develops first syptoms (e.g. chronic croakiness or hemoptysis). But if the lung cancer is detected early, there is a survival rate at 47% according to the American Cancer Society. At the same time the standard x-ray examination of the lung is the most frequently x-ray examination with a 50% share. Indeed the random detection of lung cancer in the early stage (stage 1) in the x-ray image is difficult. It is a fact that round lesions vary from 5-10 mm are easily overlooked. The routine application of CAD Chest Systems may help to detect small changes without initial suspision.
As previously stated, " Early detection increases the chance of saving lives." According to the stats on lung cancer, the survival rate of lung cancer if detected early is 47%. If lung cancer is detected late, the survival rate is decreased significantly. The potential of lung cancer identifiying lesions as cancerous in the lungs is very important. Hopefully, over-time, the diagnosis of lung cancer using CAD will improve.
CAD is available for detection of colorectal polyps in the colon. Polyps are small growths that arise from the inner lining of the Colon (anatomy). CAD detects the polyps by identifying their characteristic "bump-like" shape. To avoid excessive false positives, CAD ignores the nromal colon wall, including the haustral fold. In early clinical trials, CAD helped radiologists find more polyps in the colon than they found prior to using CAD.
This was a very interesting topic. Amazingly, a lot of men don't like taking tests for colon cancer because it is a little evasive; in terms of how the test is given, but if a test for colon cancer can save a life, it's best to have the test, as you get up in age. In the future, CAD will become less invasive than current techniques. In the future, a tiny light probe will be inserted into the rectum and will not have to go far in. It will use the light to identify cancer forming tumors etc. Amazingly, the probe is 90 percent accurate in detecing if cancerous polyps will form.
CADx is available for nuclear medicine images. Commercial CADx systems for the diagnosis of bone metastases in whole-body bone scans are coronary artery disease in myocardial perfusion images exist.
Radiology, Medical Imaging, Magnetic Resonance Imaging, Medical Ultrasound
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Illustration of the correct detection (arrowhead) by computer of a fractured vertebra (dotted circles) below the diaphragm on a lateral chest radiograph, which can be used as a second opinion.
In my opinion, Computer Aided Diagnosis is a very useful and interesting technology. Although it's a very young technology, it's very useful in helping to detect certain types of tumors and cancers etc. It doesn't have a 100% accuracy, but it's still effective in finding abnormalties in the human body and overtime, the accuracy will improve. Currently, the rate of accuracy can go as high as 90%. Basically, CAD is being used as a second opinion for radiologists, in evaluating abnormalties in the body: cancers, lumps, tumors etc. The graphic above illustrates the potential of this technology. In my opinion for patients, using human evaluations and CAD makes the diagnosis of abnormalties more accurate. What I also found intriguing was the use of CAD in detecting polyps. CAD actually helped radiologists find more polpys in the colon than they had prior to using CAD. Once again, this proves the future potential of using CAD. In the future, I have faith that this technology will only improve.
Coronary artery disease
CAD is available for the automatic detection of significant (causing more than 50% stenosis) coronary artery disease in coronary CT angiography (CCTA) studies. A low false positives rate (60-70% specificity per patient) allows using CAD as a screening device distinguishing between positive and negative studies and yielding a preliminary report. This, for example, can be used for chest pain patients' triage in an emergency setting.
Congenital heart defect
Early detection of pathology can be the difference between life and death. CADe can be done by auscultation with a digital stethoscope and specialized software, also known as Computer-aided auscultation Murmurs, irregular heart sounds, caused by blood flowing through a defective heart, can be detected with high sensitivity and specificity. Computer-aided auscultation is sensitive to external noise and bodily sounds and requires an almost silent environment to function accurately.
The University of Chicago Medical Center definition of CAD
Computer-aided diagnosis (CAD) is a broad concept that integrates image processing, computer vision, mathematics, physics, and statistics into computerized techniques that assist radiologists in their medical decision-making processes. Such techniques include the detection of disease and anatomic structures of interest, the classification of lesions, the quantification of disease and anatomic structures (including volumetric analysis, disease progression, and temporal response to therapy), risk assessment, and physiologic evaluation. Faculty in the Department of Radiology, along with their colleagues in numerous other departments, are conceptualizing and developing novel CAD methodologies. Active research projects span nearly all imaging modalities (radiography, computed tomography, ultrasound, magnetic resonance imaging, and radionuclide imaging) across a wide-range of anatomic systems (pulmonary, breast, skeletal, cardiac, gastrointestinal, neurologic, vascular, and genitourinary). These techniques seek to maximize the information that may be extracted from medical images by augmenting radiologists subjective, qualitative interpretation of the displayed images with objective, quantitative computations of the underlying numeric image data.
My Personal Summary of Computer-aided diagnosis
Personally, I view Computer-aided diagnosis as a good technique used to assist radiologists. Basically, I see it as a computerized way to reinforce doctors' ideas about a particular initial diagnosis that they made using regular medical images. Aside from that, it goes much deeper than that. CAD pretty much pinpoints problematic areas that are infected with disease and even analyzes that area on many different levels using advanced numeric calculations. To me, this important because it helps the radiologists to strategize on a way to treat the patient and understand the potential progression of the disease. Even though some say this particular method is not completely 100% accurate, it's clear to me that this technology is more helpful than harmful. In the not to distant future, I see this method becoming even more accurate than it already is as technology advances.
Potential of Computer-aided diagnosis in the future
In regards to the potential future effects Computer-aided diagnosis will have on health information technology, CAD's will continue to evolve along with image processing software that is associated with the workstation specified for the particular image processors. Some examples of this would be mammograms, CT's, and MRI's. The growing fusion of CAD's and PAC's which are
ystems. Images within the system will be uploaded for future reference and can be used by healthcare professionals before making final decisions after they have studied the images. This technology will be most helpful to radiologists considering the fact that they use imaging to both and treat potential threats within the body. With the computer output of the CAD's the time radiologist spend reading images can be cut significantly. The early detection of breast cancer via mammograms is only the tip of the iceberg as far as CAD's go.
Basic Concept of Computer -aided diagnosis
The computer-aided diagnosis purpose is to improve the accuracy of image interpretation as well as its consistency using the computer output. They help radiologist better interpret the normal and abnormal features on the image that is provided. CAD's include three basic components. For starters, the first component would be image processing. This is done to enhance and extract lesions. The second component is the quantification of image features. These features include size, shape, and contrast of images interpreted in the previous component. Thirdly, the last component is data processing. The data that is being processed are the images that have been interpreted and the finding of distinctions between normal and abnormal patterns. The basic concept of computer-aided diagnosis is quite broad and is applicable to all imaging mods. Schemes can be created for every body part examination.
Challenges of Computer-aided diagnosis
One of the glaring problems with computer-aided diagnosis is that databases don't have an adequate number of cases for researchers to base there findings off of. Another is the automation level of the segmentation techniques. Though it is a sub component to the overall system, the usability of the segmentation techniques is important in grading the overall accuracy and effectiveness of the system in regards to making a diagnosis. Also when targeting small nodules problems arise. This may occur due to spacial discretizating used during CT imaging. Another is developing a CAD scheme that is reliable as well as meet the approval of the FDA for clinical use. Small companies often find it difficult because of the required clinical studies that are needed for pre-market approval. The lengthiness and the cost of such research discourages the small companies and leads them to rely on the current technology that they have accessible to them.
My Personal Summary of Computer-aided diagnosis
Though computer-aided diagnosis is mostly used in radiology for early detection for lung and breast cancer, I believe it has the potential to effect other areas of medicine in regards to early detection of diseases. In the years to come once there is enough data and a proper database is developed, this technology has the chance to change the efficiency and time spent by medical professionals around the world analyzing images of their patients. Doctors will able to go to the database of a CAD and study other cases that were similar to the current case or even detect in younger children if they are at risk for a particular disease based on there relatives images and be able to combat or even destroy the disease before it even becomes any concern to the patient. Though CAD's have the capability of assisting MD's on a variety of medical cases in the future, I believe it is still in the hands of the doctor to properly analyze what the CAD provides them along with their research to make the final decision when it comes to potential saving a patients life.
Medical pre-market approval,
FDA(Food and Drug Administration), Segmentation
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