Computer-assisted diagnosis system for breast cancer in computed tomography laser mammography (CTLM)

Computed tomography laser mammography (Eid et al. Egyp J Radiol Nucl Med, 37(1): p. 633–643, 1) is a non-invasive imaging modality for breast cancer diagnosis, which is time-consuming and challenging for the radiologist to interpret the images. Some issues have increased the missed diagnosis of radiologists in visual manner assessment in CTLM images, such as technical reasons which are related to imaging quality and human error due to the structural complexity in appearance. The purpose of this study is to develop a computer-aided diagnosis framework to enhance the performance of radiologist in the interpretation of CTLM images. The proposed CAD system contains three main stages including segmentation of volume of interest (VOI), feature extraction and classification. A 3D Fuzzy segmentation technique has been implemented to extract the VOI. The shape and texture of angiogenesis in CTLM images are significant characteristics to differentiate malignancy or benign lesions. The 3D compactness features and 3D Grey Level Co-occurrence matrix (GLCM) have been extracted from VOIs. Multilayer perceptron neural network (MLPNN) pattern recognition has developed for classification of the normal and abnormal lesion in CTLM images. The performance of the proposed CAD system has been measured with different metrics including accuracy, sensitivity, and specificity and area under receiver operative characteristics (AROC), which are 95.2, 92.4, 98.1, and 0.98%, respectively

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

Data-Driven Model for Upper Limb Spasticity Detection

Healthcare providers in the field of physical and rehabilitation medicine play a vital role to help patients suffering spasticity readapting themselves to their normal daily activities. Mathematical modeling of spasticity has the potential to avoid the issue of variability in the assessment of spasticity using the Modified Ashworth scale (MAS). In this work, an existing mathematical model for upper limb spasticity is verified using clinical data sets of upper limb spasticity collected in Malaysia at the level of MAS 1+. The data set consists of torque values measured at each elbow angle as the elbow extends from a full flexion position to a full extension position during slow and fast stretch of the forearm. The aim is to find out the capability of the mathematical model and lay a foundation for the future work on data-driven modeling of upper limb spasticity based on the Modified Ashworth Scale

ANALYSIS OF PLANT FRAGARIA XANANASSA DISEASE DIAGNOSES USING PRODUCTION RULES BASE ON EXPERT SYSTEM

Errors that occur in solving problems in strawberry plants (Fragaria Xananassa) such as the presence of leaf patches, fruit rot, perforated leaves, and insect pests can be the cause of not maximum in harvest time. The farmers and the general public who planted strawberry (Fragaria Xananassa) need to know the proper treatment of diseases and pests so that future yields as expected. Therefore, it takes an application as a solution in the delivery of information related to the problems that are often encountered in strawberry plants (Fragaria Xananassa). Methods of production rules can be used to diagnose the disease strawberry (Fragaria Xananassa) based on signs or symptoms that occur in the parts of plants and strawberry, the results of diagnosis using this method are the same as we do Consultation on experts.  The purpose of this study was to determine the early diagnosis of disease in strawberry plants (Fragaria Xananassa) based on signs or symptoms that occur in the plant and fruit parts. The results of the analysis of this study showed that the validation of disease and symptom data in strawberry plants (Fragaria Xananassa) reached 99%, meaning that between the data of symptoms and disease understudy the accuracy was guaranteed with the experts

Analysis of Expert System for Early Diagnosis of Disorders During Pregnancy Using the Forward Chaining Method

oai:ojs.ijair.id:article/203Nowadays technological developments are increasingly having a positive influence on the development of human life, including in the health sector. One of them is an expert system that can transfer an expert's knowledge into a computer application to simplify and speed up the diagnosis of a disorder or disease in humans. The purpose of this final project is to design an application to diagnose diseases that occur during pregnancy which is caused by the existence of these pregnancies to simplify and speed up the diagnosis of diseases experienced by pregnant women. This study uses the forward chaining method. By involving experts in this expert system analysis according to current needs. Users are given easy access to information on several types of pregnancy disorders and their symptoms, as well as consultation through several questions that the user must answer to find out the results of the diagnosis. While experts are facilitated in system management, both the process of adding, updating and, deleting data

Review of optical breast imaging and spectroscopy

Diffuse optical imaging and spectroscopy of the female breast is an area of active research. We review the present status of this field and discuss the broad range of methodologies and applications. Starting with a brief overview on breast physiology, the remodeling of vasculature and extracellular matrix caused by solid tumors is highlighted that is relevant for contrast in optical imaging. Then, the various instrumental techniques and the related methods of data analysis and image generation are described and compared including multimodality instrumentation, fluorescence mammography, broadband spectroscopy, and diffuse correlation spectroscopy. We review the clinical results on functional properties of malignant and benign breast lesions compared to host tissue and discuss the various methods to improve contrast between healthy and diseased tissue, such as enhanced spectroscopic information, dynamic variations of functional properties, pharmacokinetics of extrinsic contrast agents, including the enhanced permeability and retention effect. We discuss research on monitoring neoadjuvant chemotherapy and on breast cancer risk assessment as potential clinical applications of optical breast imaging and spectroscopy. Moreover, we consider new experimental approaches, such as photoacoustic imaging and long-wavelength tissue spectroscopy

Diffuse Optical Tomography Imaging of Chemotherapy-Induced Changes in Breast Tissue Metabolism

Breast cancer is fast becoming the leading cause of mortality in women worldwide. As of this year, there are more than 3.1 million women with a history of breast cancer in the U.S., and about 41,760 women are expected to die from this disease. Neoadjuvant chemotherapy (NAC) has become a well-established therapy in the treatment of patients with locally advanced or primarily inoperable breast cancer. It consists of 3-9 months of drug treatment to shrink the tumor size before surgical removal of any remaining mass. A pathological complete response (pCR) is defined as complete disappearance of the tumor before surgery and correlates with 5-year overall survival of the treated patient. However, only 15-40% of subjects who undergo NAC will achieve a pCR, while the remaining patients do not benefit from a therapy that has considerable side effects. In this Ph.D. thesis, I explore the potential of diffuse optical tomography (DOT) for breast cancer imaging and NAC monitoring. The overall objective is two-fold. First, I seek to identify breast cancer patients who will not respond to NAC shortly after the initiation of a 5-9 months therapy regimen. Identifying these patients early will allow a switch to a more promising therapy and avoiding months of ineffective therapy with a drug regimen that has considerable side effects. Second, I use the optical data simultaneously obtained from the contralateral, non-tumor bearing breast to better understand the factors that modulate breast density and the source of its contrast in DOT. This work analyzed DOT data from 105 patients with stage II-III breast cancer under NAC regimen. Data processing and image analysis protocols were developed to more effectively evaluate static tissue contrast and dynamic functional imaging of the breast. Notably, we observed that there are differences in the time evolution of DOT features between pCR and non-pCR tumors under NAC, and DOT features can contribute to the successful prediction of pCR status from pretreatment imaging. Lastly, our analysis demonstrated a positive correlation between DOT feature and mammographic density classification, which could lead to research on the potential use of DOT as a predictor of breast cancer as well as an assessment tool to longitudinally evaluate the efficacy of chemoprevention strategies. These findings represent important steps towards the translation of DOT into current clinical workflow to contribute to better-personalized breast cancer therapies and breast cancer risk management

Optical Contrast Agents to Visualize Molecular Expression in Breast Cancer

Breast cancer is the second leading cause of death of women in the United States. Improvements in screening technology have increased the breast cancer incidence rate, as smaller lesions are being detected. Due to the small size of lesions, patients can choose to receive breast conservation therapy (BCT) rather than a modified radical mastectomy. Even though the breast retains cosmesis after BCT, there is an increased risk of the patient having residual microscopic disease, known as positive margins. Patients with positive margins receive increased radiation and have an increased chance of second surgery. Pathology with hematoxylin and eosin (H&E) remains the gold standard for diagnosing margin status in patients. Intraoperative pathology has been shown to reduce the rate of positive margins in BCT. However, a minority of surgery centers have intraoperative pathology centers, limiting the number of patients that receive this standard of care. The expression profiles of surface receptors such as ErbB2 (HER2-positive) and epidermal growth factor receptor (EGFR) provide information about the aggressiveness of a particular tumor. Recent research has shown that there was elevated EGFR expression in patients with a local recurrence even though the biopsies were assessed to be disease free using standard H&E. If the physicians had known the molecular expression of these biopsies, a different treatment regimen or excision of more tissue might have prevented the recurrence. This thesis investigates targeted molecular contrast agents that enhance the visualization of molecular markers such as glucose transporters (GLUTs) and growth factor receptors in tissue specimens. First, application of 2-NBDG, a fluorescent deoxy-glucose, enhances signal in cancerous tissue with a 20-minute incubation. Then, antibody functionalized silica-gold nanoshells enhance the visualization of ErbB2 overexpression in specimens with a 5-minute incubation. To image these contrast agents in cancerous tissue, a portable, inexpensive device was developed as a tool to help physicians visualize expression of surface markers. The system visualizes absorbance from nanoshell aggregates and fluorescence in the visible and near-infrared light spectrum. This study represents the first step in the development of an intraoperative optical imaging device to enhance the visualization of molecular markers overexpressed in cancerous cells