Review of Different Methods of Abnormal Mass Detection in Digital Mammograms

Various images from massive image databases extract inherent, implanted information or different examples explicitly found in the images. These images may help the community in initial self-screening breast cancer, and primary health care can introduce this method to the community. This study aimed to review the different methods of abnormal mass detection in digital mammograms. One of best methods for the detection of breast malignancy and discovery at a nascent stage is digital mammography. Some of the mammograms with excellent images have a high intensity of resolution that enables preparing images with high computations. The fact that medical images are so common on computers is one of the main things that helps radiologists make diagnoses. Image preprocessing highlights the portion after extraction and arrangement in computerized mammograms. Moreover, the future scope of examination for paving could be the way for a top invention in computer-aided diagnosis (CAD) for mammograms in the coming years. This also distinguished CAD that helped identify strategies for mass widely covered in the study work. However, the identification methods for structural deviation in mammograms are complicated in real-life scenarios. These methods will benefit the public health program if they can be introduced to primary health care's public health screening system. The decision should be made as to which type of technology fits the level of the primary health care system

No less than a women: improving breast cancer detection & diagnosis

Breasts, being the ultimate symbol of femininity, make breast cancer one of the most traumatic events any woman could ever face. Perhaps it is this sense of pride in these attributes that makes many women reluctant to discuss and share their experiences with breast cancer. Many may feel that their absolute core identity has been shaken, making them less than a woman. The fear and stigma attached to this disease are currently among the major difficulties faced by healthcare providers in convincing women to effectively manage their breast disease. It may leave women feeling isolated and as a result, withdrawing from society and even life- making them feel less than a woman. Beyond the stigma and mental anguish there is also the tremendous stress of going through a number of surgeries, chemotherapies and radiation therapies, with the risk of treatment failure and recurrence always at the back of their minds. Fortunately various studies confirm that early breast cancer detection saves lives, reduces medical treatments and costs, and ultimately, gives one hope for a better future. The availability of effective screening reduces the mortality from breast cancer by up to 50%. Most women will be lucky enough to never develop breast cancer, but for the many of those who do, their lives may be saved by advanced detection. Currently, breast cancer detected at an early stage can be treated appropriately, with most being cured. The role of a health care provider is therefore extremely important, in counselling and motivating women to overcome their fears and come forward for regular examinations. The role of a radiologist is equally important in synergizing imaging modalities towards achieving the best of medical care for the public. These are some of the ways to help and support in the management of the disease and in making the ladies feel no less than a woman. In order to reach a superior level in early detection and diagnosis of breast cancer, our research team studied various methods to overcome some of the limitations in breast imaging. These methods include Computer Aided Diagnosis techniques involving various existing imaging modalities such as mammogram, tomosynthesis, breast ultrasound, computed tomography laser mammography (CTLM) and thermography of the breast. More rewarding research on newer imaging devices includes the ultra-wide band (UWB) imaging of the breast. Recent usage of a computational model involving Monte Carlo Simulation for early breast cancer detection using wire mesh collimator gamma camera in scintimammography is also gaining interest amongst clinicians

Skin Lesion Extraction And Its Application

In this thesis, I study skin lesion detection and its applications to skin cancer diagnosis. A skin lesion detection algorithm is proposed. The proposed algorithm is based color information and threshold. For the proposed algorithm, several color spaces are studied and the detection results are compared. Experimental results show that YUV color space can achieve the best performance. Besides, I develop a distance histogram based threshold selection method and the method is proven to be better than other adaptive threshold selection methods for color detection. Besides the detection algorithms, I also investigate GPU speed-up techniques for skin lesion extraction and the results show that GPU has potential applications in speeding-up skin lesion extraction. Based on the skin lesion detection algorithms proposed, I developed a mobile-based skin cancer diagnosis application. In this application, the user with an iPhone installed with the proposed application can use the iPhone as a diagnosis tool to find the potential skin lesions in a persons\u27 skin and compare the skin lesions detected by the iPhone with the skin lesions stored in a database in a remote server

Depth Segmentation Method for Cancer Detection in Mammography Images

Breast cancer detection remains a subject matter of intense and also a stream that will create a path for numerous debates. Mammography has long been the mainstay of breast cancer detection and is the only screening test proven to reduce mortality. Computer-aided diagnosis (CAD) systems have the potential to assist radiologists in the early detection of cancer. Many techniques were introduced based on SVM classifier, spatial and frequency domain, active contour method, k-NN clustering method but these methods have so many disadvantages on the SNR ratio, efficiency etc. The quality of detection of cancer cells is dependent with the segmentation of the mammography image. Here a new method is proposed for segmentation. This algorithm focuses to segment the image depth wise and also coloured based segmentation is implemented. Here the feature identification and detection of malignant and benign cells are done more easily and also to increase the efficiency to detect the early stages of breast cancer through mammography images. In which the relative signal enhancement technique is also done for high dynamic range images. Markovian random function can be used in the depth segmentation. Markov Random Field (MRF) is used in mammography images. It is because this method can model intensity in homogeneities occurring in these images. This will be helpful to find the featured tumor DOI: 10.17762/ijritcc2321-8169.15023

Three-dimensional reconstruction of peripheral nerve internal fascicular groups

Peripheral nerves are important pathways for receiving afferent sensory impulses and sending out efferent motor instructions, as carried out by sensory nerve fibers and motor nerve fibers. It has remained a great challenge to functionally reconnect nerve internal fiber bundles (or fascicles) in nerve repair. One possible solution may be to establish a 3D nerve fascicle visualization system. This study described the key technology of 3D peripheral nerve fascicle reconstruction. Firstly, fixed nerve segments were embedded with position lines, cryostat-sectioned continuously, stained and imaged histologically. Position line cross-sections were identified using a trained support vector machine method, and the coordinates of their central pixels were obtained. Then, nerve section images were registered using the bilinear method, and edges of fascicles were extracted using an improved gradient vector flow snake method. Subsequently, fascicle types were identified automatically using the multi-directional gradient and second-order gradient method. Finally, a 3D virtual model of internal fascicles was obtained after section images were processed. This technique was successfully applied for 3D reconstruction for the median nerve of the hand-wrist and cubital fossa regions and the gastrocnemius nerve. This nerve internal fascicle 3D reconstruction technology would be helpful for aiding peripheral nerve repair and virtual surgery.Yingchun Zhong, Liping Wang, Jianghui Dong, Yi Zhang, Peng Luo, Jian Qi, Xiaolin Liu and Cory J. Xia