A SURVEY ON MELANOMA DETECTION ON DERMOSCOPIC SKIN LESION IMAGES USING ROC METHOD Subtitle as needed
A SURVEY ON MELANOMA DETECTION ON DERMOSCOPIC SKIN LESION IMAGES USING ROC METHOD
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Abstract—This Melanoma Mortality Rates (MMR) is highest amongst skin cancer patients and thus melanoma is life threatening, when it grows beyond the dermis of the skin. It is dangerous, when compared to other type of skin cancer. It is a condition or disorder that develops from melanocytes pigment known as melanin. Here Skin Cancer is detected in early stages using Non Invasive Computerized Dermoscopy and analyze the images using Receiver Operating Characteristics (ROC) and Artificial Neural Network (ANN).The algorithm follows three steps: First Lesions are extracted using a self-generating Neural Network (SGNN), Second feature descriptive of tumour size texture and border are extracted and third lesion objects are classified by their stages. The dermoscopic images contain lesions that are large enough for further research. Thus the sensitivity and accuracy of the proposed system will be more efficient when compared to the computerized dermoscopy method. Various Parameters such as shape, size, texture, colour and its properties will be calculated. And the accurate skin affected region which is the skin lesion or region of interest will be taken out for computerized surgery. PH2 dataset is used for producing the results.
Keywords—component; SVM , k means, Neural Networks, Segmentation
Image processing is a method to convert an image into digital form and perform operations on it and in order to get an enhanced image or to extract some useful information from it. It is a type of signal dispensation in which input is image, like video frame or photograph and output may be image or characteristics associated with that image. Usually Image Processing system includes treating images as two dimensional signals while applying already set signal processing methods to them. It is among rapidly growing technologies today, with its applications in various aspects of a business. Image Processing forms core research area within Engineering and
Computer Science disciplines too .
Image processing basically includes the following three steps 1. Importing the image with optical scanner or by digital photography. 2. Analysing and manipulating the image which includes data compression and 3.image Enhancement and spotting patterns that are not to human eyes like satellitephotographs.4. Output is the last stage in which result can be altered image or report that is based on image analysis.
B.TYPES OF IMAGE PROCESSING
The two types of methods used for Image Processing are Analog and Digital Image Processing. Analog or visual techniques of image processing can be used for the hard copies like printouts and photographs. Image analysts use various fundamentals of interpretation while using these visual techniques. The image processing is not just confined to area that has to be studied but on knowledge of analyst. Digital Processing techniques help in manipulation of the digital images by using computers. As raw data from imaging sensors from satellite platform contains deficiencies. To get over such flaws and to get originality of information, it has to undergo various phases of processing. The three general phases that all types of data have to undergo while using digital technique are Pre- processing, Enhancement and Display, information extraction.
C.CHARACTERSTICS OF IMAGE PROCESSING
Before processing an image, it is converted into a digital form. Digitization includes sampling of image and quantization of sampled values. After converting the image into bit information, processing is performed. This processing technique maybe Image enhancement, Image restoration and Image compression
Image enhancement It refers to accentuation or sharpening of image features such as boundaries or contrast to make a graphic display more useful for display & analysis. This process does not increase the inherent information content in data. It includes gray level &contrast manipulation, noise reduction, edge crispening and sharpening, filtering, interpolation and magnification, pseudo colouring, and so on .Image restoration It is concerned with filtering the observed image to minimize the effect of degradations. Effectiveness of image restoration depends on the extent and accuracy of the knowledge of degradation process as well as on filter design. Image restoration differs from image enhancement in that the latter is concerned with more extraction or accentuation of image features.
Image compression: It is concerned with minimizing the number of bits required to represent animate. Application of compression are in broadcast TV, remote sensing via satellite, military communication via aircraft, radar, teleconferencing, facsimile transmission, for educational & business documents, medical images that arise in computer3tomography, magnetic resonance imaging ,digital radiology, motion pictures, satellite images, weather maps, geological surveys and so on. Text compression – CCITT GROUP3 & GROUP4 Still image compression – JPEG Video image compression – MPEG
Cancer is a group of diseases involving abnormal cell growth with the potential to invade or spread to other parts of the body. These contrast with benign tumors, which do not spread to other parts of the body. Possible signs and symptoms include a lump, abnormal bleeding, prolonged cough, unexplained weight loss, and a change in bowel movements While these symptoms may indicate cancer, they may have other causes. Over 100 types of cancers affect humans. There are many type of cancer ,some of them are Breast cancer ,Thyroid cancer ,Lung cancer, Skin cancer, Brain cancer ,Cervical cancer, Uterine cancer ,Liver cancer etc.
In present technology Digital Image Processing plays a major role in every field particularly Image Processing with biomedical image analyzes plays a major role so in order to give importance to an image processing we are moving with the biomedical imaging techniques .In biomedical techniques there are different types for example: skin cancer liver processing ,brain tumor analysis .I am concentrating on skin cancer .Due to present food system and environmental imapact more no of people affected by the skin cancer .So in order to analyze the effect of skin cancer and types and its classification and also to increase the process of doctor .
E. SKIN CANCER
36417251957070Skin cancers are cancers that arise from the skin. They are due to the development of abnormal cells that have the ability to invade or spread to other parts of the body. There are three main types of skin cancers: Basal Cell Carcinoma (BCC), Squamous Cell Carcinoma (SCC) and melanoma. The first two along with a number of less common skin cancers are known as Non-Melanoma Skin Cancer (NMSC). Basal-Cell cancer grows slowly and can damage the tissue around it but is unlikely to spread to distant areas or result in death. It often appears as a painless raised area of skin that may be shiny with small blood vessel running over it or may present as a raised area with an ulcer. Squamous-cell skin cancer is more likely to spread. It usually presents as a hard lump with a scaly top but may also form an ulcer. Melanomas are the most aggressive. Signs include a mole that has changed in size, shape, color, has irregular edges, has more than one color, is itchy or bleeds.
A.SURVEY OF SKIN CANCER IN INDIA
Australia and New Zealand have the highest incidence and mortality rates of melanoma in the world, according to Australia’s Department of Health and Aging. In those two countries, the risk of developing melanoma before the age of 75 is 1 in 24 for males and 1 in 34 for females Each year in the U.S. over 5.4 million cases of non-melanoma skin cancer are treated in more than 3.3 million people. Each year there are more new cases of skin cancer than the combined incidence of cancers of the breast, prostate, lung and colon. Over the past three decades, more people have had skin cancer than all other cancers combined. One in five Americans will develop skin cancer in the course of a lifetime. Between 40 and 50 percent of Americans who live to age 65 will have either basal cell carcinoma or squamous cell carcinoma at least once. Basal Cell Carcinoma (BCC) is the most common form of skin cancer. Squamous Cell Carcinoma is the second most common form of skin cancer. More than 1 million cases are diagnosed in the U.S. each year. Organ transplant patients are approximately 100 times more likely than the general public to develop squamous cell carcinoma. Actinic keratosis is the most common pre-cancer; it affects more than 58 million Americans. About 90 percent of non-melanoma skin cancers are associated with exposure to Ultra Violet (UV) radiation from the sun. The annual cost of treating skin cancers in the U.S. is estimated at $8.1 billion: about $4.8 billion for non-melanoma skin cancers and $3.3 billion for melanoma.
One person dies of melanoma every hour (every 54 minutes). An estimated 6 87,110 new cases of invasive melanoma will be diagnosed in the U.S. in 2017.An estimated 9,730 people will die of melanoma in 2017.Melanoma account for less than one percent of skin cancer cases, but the vast majority of skin cancers death. The vast majority of melanomas are caused by the sun. In fact, one U.K. study found that about 86 percent of melanomas can be attributed to exposure to ultraviolet (UV) radiation from the sun. The estimated 5-year survival rate for patients whose melanoma is detected early is about 98 percent in the U.S. The survival rate falls to 62 percent when the disease reaches the lymph nodes, and 18 percent when the disease metastasizes to distant organs. On average ,a person’s risk for melanoma doubles if he or she has had more than five sunburns .Regular daily use of an SPF 15 or higher sunscreen reduces the risk of developing squamous cell carcinoma by about 40 percent and the risk of developing melanoma by 50 percent.
b) Equipment used for skin cancer treatment
Most skin cancer cases are treated in a dermatologist’s office. But if you have melanoma, or if your non-melanoma skin cancer is more advanced, consider all your treatment options before deciding on a care plan. At all the hospitals, we offer innovative treatments and technologies all under one roof are offered. Cancer experts evaluate the type and stage of the skin cancer, and then develop a comprehensive treatment plan tailored to the needs and diagnosis. Individualized plan may include medical treatments and technologies combined with supportive care services designed to help reduce side effects.
c) Skin cancer diagnostic evaluations
A skin cancer diagnosis usually begins with a visual examination. The Skin Cancer Foundation and the American Cancer Society recommend monthly self examinations and annual doctor visits to screen for potential skin cancer. If a suspicious spot is found, the doctor will first examine the area, noting its size, shape, color and texture, as well as any bleeding or scaling. The doctor may also examine nearby lymph nodes to see whether they are enlarged. If seen by a primary care physician, the patient may be referred to a dermatologist who can perform more specialized tests and make a diagnosis.
d) Biopsy for skin cancer
During a biopsy, a doctor removes a sample of tissue or fluid from the body. A pathologist inspects the cells under a microscope to see if they are cancerous. Some biopsies are performed endoscopically, others under image guidance such as ultrasound, Computed Tomography (CT) or Magnetic Resonance Imaging (MRI) in the radiology suite. In some cases, biopsies are performed in the operating suite. This allows the doctor to collect tissue from deep inside the body. Depending on the type of biopsy performed, the patient may receive an anesthetic to reduce discomfort. Biopsies provide tissue samples for diagnosis and may help determine whether the cancer began at the site of the biopsy sample, or if it started somewhere else in the body. Some sites that are commonly biopsied include the breast, skin, bone marrow, GI tract, lung, liver, bladder, colon and lymph nodes. The doctors determine the appropriate method of biopsy based on several factors, such as the size, shape, location, and characteristics of the abnormality
e) Imaging for skin cancer
Most skin cancers especially Basal Cell Carcinoma, the most common form of skin cancer remain local and do not spread to distant organs. Melanoma and Merkel Cell Carcinoma are more prone to spread. In those cases, one of several medical imaging procedures may be used to determine whether cancer cells have metastasized to internal organs and bones. Imaging procedures include: CT scan, X-ray, and MRI. These imaging procedures are non-invasive and painless. If they reveal suspicious spots or metastases a more invasive biopsy may be required.
f) Skin cancer advanced medical treatments
Most cases of skin cancer may be treated in a dermatologist’s office or with outpatient surgery. But more aggressive skin cancers, such as melanoma or Merkel Cell Carcinoma, may require more extensive treatments, such as surgery, chemotherapy or immunotherapy. The multidisciplinary team of doctors and clinicians at Cancer Treatment Centers of America (CTCA) will answer the questions and recommend treatment options based on your unique diagnosis. The advanced medical treatment equipment is Surgery, Chemotherapy, Targeted Therapy, Topical Treatments, Immunotherapy, Radiation therapy.
g) Dermatoscopy method
The essential tool for dermatologists, is the Dermoscopy method and it is also the non –invasive method .To evaluate pigmented lesions, the
abnormal structural features of melanoma can be identified using dermoscopy .Benign lesions can be confidently diagnosed without need
for biopsy.Sensitivity and Specificity for detection of melanoma increases the accuracy of diagnosis with dermoscopy performed by experts
Types of dermatoscopy
A Dermatoscope is composed of a transilluminating light source and a magnifying optic(usually a 10-fold magnification).There are three main modes of dermoscopy: Nonpolarized light ,contact ,Polarized light ,contact ,Polarized light ,noncontact.
Polarized light allows for visualization of deeper skin structures, while non-polarized light provide information about the superficial skin .Most modern dermatoscopes allow the user to toggle between the two modes, which provide complementary information.
Advantages of dermatoscopy
The diagnostic accuracy for melanoma is significantly better when compared to expert doctors in the field of dermatoscopy. There is considerable improvement in the sensitivity or detection of malignant melanomas as compared with the traditional clinical naked eye examination. Using Dermatoscopy method the specificity is increased and it reduced the frequency of unnecessary surgical excisions of benign lesions.
Applications of dermatoscopy
Digital dermatoscopy (videodermatoscopy) is used for monitoring skin lesions suspicious of melanoma .Digital dermatoscopy images are stored and compared to images obtained during the patient’s next visit. Suspicious changes in such a lesion are an indication for excision. Skin lesions which appear unchanged over time, are considered benign.
COMPUTER-AIDED DIAGNOSIS OF MELANOMA USING BORDER- AND WAVELET-BASED TEXTURE
Contribute extra features in such a way as to emphasize their qualities with border and geometry features are compares with
texture information, and higher contribution of texture features than border-based features in the optimized feature set.
However, the authors acknowledge that due to lack of a standard benchmark for dermoscopy (melanoma) imaging, it is not easily feasible to provide a comprehensive and quantitative comparative study among the existing classification methods.
ACCURATE SEGMENTATION OF DERMOSCOPIC IMAGES BY IMAGE THRESHOLDING BASED ON
TYPE- 2 FUZZY LOGIC
It is observed that the presented method exhibits superior performance over competing methods and is very successful at handling the uncertainty encountered in determining the border between the lesion and the skin.
The adaptive thresholding method exhibits very poor performance when the lighting condition is poor or non uniform. In this case, the adaptive thresholding method does not yield an acceptable border at all.
DETECTION AND ANALYSIS OF IRREGULAR STREAKS IN DERMOSCOPIC IMAGES OF SKIN LESIONS
Orientation estimation and correction is applied to detect low contrast and fuzzy streak lines and the detected line segments are used to
extract clinically inspired feature sets for orientation analysis of the structure.
Irregular streak method leads to slow process and with taking huge dataset.
TWO SYSTEMS FOR THE DETECTION OF MELANOMAS IN DERMOSCOPY IMAGES USING TEXTURE
AND COLOR FEATURES
Local features and global features are estimated for colour and texture only
Since colour and texture has been estimated, we need to detect the stage of the melanoma which is not done here.
A COMPARISON OF FEATURE SETS FOR AN AUTOMATED SKIN LESION ANALYSIS SYSTEM FOR
MELANOMA EARLY DETECTION AND PREVENTION
An automated image analysis method analysis module which contains image acquisition, hair detection, and exclusion, lesion segmentation, feature extraction and classification
From feature extraction several values have to be analysed which has not been done here..eg: mean standard deviation image, mask,fixing a threshold level.
OVERVIEW OF ADVANCED COMPUTER VISION SYSTEMS FOR SKIN LESIONS CHARACTERIZATION
Computer based vision diagnosis system aiming mostly at the early detection of the skin cancer and more specifically, the recongnition of malignant melanoma tumor.
Clinical decision support systems (CDSS) used is less expenses than other hardware and software acquisition.
This method is more difficult for primary physicians and general practitioners. However computer-based vision systems are not yet established in routine clinical practice for skin diagnosis and prognosis, probably because they are not performing convincingly in all cases of the skin pathology.
SKIN CANCER DETECTION USING IMAGE PROCESSING
This paper proposed skin cancer detection of cancer disease and it is more advantageous to patients. Diagnosing methodology uses Image Processing method and Support Vector Machine (SVM) algorithm.
A Biopsy method is a method to remove a piece of tissue or a sample of cells from patient body so that it can be analysed in the
It is a uncomfortable method.
Biopsy method is a time consuming for patient as well as doctor because it takes lot of time for testing.
There is a possibility of spreading of disease to other parts of the body.
It is more risky.
TITLE AUTHOR NAME TECHNIQUE Computer- Aided Diagnosis Of Melanoma Using Border And Wavelet Based – Texture Analysis Rahil Garnavi
James Bailey Computer aided diagnosis ADVANTAGES: Contribute extra features in such a way as to emphasize their qualities with border and geometry features are compares with texture information, and higher contribution of texture features than border-based features in the optimized feature set.
DISADVANTAGES: However, the authors knowledge that due to lack of a standard benchmark for dermoscopy (melanoma) imaging, it is not easily feasible to provide a comprehensive and quantitative comparative study among the exsisting classification methods.
Accurate Segmentation of Dermoscopic Images by Image Thresholding based on type- 2 fuzzy logic.
Murat Borlu A novel thresholding- based segmentation approach ADVANTAGES: It is observed that the presented method that exhibits superior performance over competing methods and is very successful at handling the uncertainity countered in determining the border between the lesion and the skin.
DISADVANTAGES: The adaptive thresholding method exhibits very poor performance when the lighting condition is poor or non uniform .In this case, the adaptive thresholding method does not yield an acceptable border at all.
A Comparison of Feature Set for an Automated skin Lesion Analysis for Melanoma Early Detection and Prevention Omar Abuzaghleh
Buket D.Barkana Real Time Alert and automated Image Analysis module ADVANTAGES: An automated image analysis method module which contains image acquisition, hair detection and exclusion, lesion segmentation, feature extraction and classification.
DISADVANTAGES: From feature extraction several values have to be analysed which has not been done here.eg: mean, standard deviation, image mask, fixing a threshold level.
Skin Cancer Detection using Image Processing Uzma Bano Ansari
Tanuja Sarode Skin Cancer Detection method ADVANTAGES: This paper proposed skin cancer detection of cancer disease and it is more advantageous to patients. Diagnosing methodology use Image Processing method and Support Vector Machine (SVM) algorithm.
DISADVANTAGES: Biopsy method is a uncomfortable method and also the time consuming method it take lots of time. It is more risky and possible of spreading disease to other parts of the body.
Overview of Advanced Computer Vision System for Skin lesion Characterization Maglogiannis I
Doukas C.N Clinical Decision Support Systems
ADVANTAGES: Computer based vision diagnosis system aiming mostly at the early detection of the skin cancer and more specifically, the recongnition of malignant melanoma tumor.
Clinical decision support systems (CDSS) used in less expenses than other software and hardware acquisition.
DISADVANTAGES: This method is more difficult for primary physicians and general practitioners. However computer-based vision systems are not yet established in routine clinical practice for diagnosis and prognosis, probably because they are not performing convincingly in all cases of the skin pathology.
The early detection of melanoma is essential for successful treatment. Because dermoscopy images are so inexpensive to obtain and so widely available, they provide the most viable option for application of new image processing and machine learning algorithms. Therefore, melanoma detection using dermoscopy images has the most potential for disruption of the current clinical paradigm of waiting until the melanoma is at a later stage and performing an excessive number of biopsies. The advent of a fast, accurate and cost-effective on-the-spot technology, in the clinic or even at home, is most likely to be afforded by the type of computer analysis of dermoscopy images described here. Dermoscopy images come with various aberrations and artifacts and hence it is crucial to follow the proper steps and methods described here to remedy these abnormalities and achieve a correct diagnosis. Lesion segmentation with acceptable tolerance allows for acceptable precision in feature segmentation which in turn helps in maximizing classification accuracy. Although lesion segmentation, feature segmentation, feature generation and classification are the major steps, proper attention should be given to the auxiliary steps which in most cases are the major contributors to an exemplary outcome
Future of the work presented here by using Artificial Neural Network (ANN) the color model ,training and testing sequence analysis will
be carried out and the PH2 database and ATLAS database used to analyse the skin lesion .
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