Design of a Low-Cost Diffuse Optical Mammography System for Biomedical Image Processing in Breast Cancer Diagnosis.

Worldwide, breast cancer is the most common type of cancer that mainly affects women. Several diagnosis techniques based on optical instrumentation and image analysis have been developed, and these are commonly used in conjunction with conventional diagnostic devices such as mammographs, ultrasound, and magnetic resonance imaging of the breast. The cost of using these instruments is increasing, and developing countries, whose deaths indices due to breast cancer are high, cannot access conventional diagnostic methods and have even less access to newer techniques. Other studies, based on the analysis of images acquired by traditional methods, require high resolutions and knowledge of the origin of the captures in order to avoid errors. For this reason, the design of a low-cost diffuse optical mammography system for biomedical image processing in breast cancer diagnosis is presented. The system combines the acquisition of breast tissue photographs, diffuse optical reflectance (as a biophotonics technique), and the processing of digital images for the study and diagnosis of breast cancer. The system was developed in the form of a medical examination table with a 638 nm red-light source, using light-emitted diode technology (LED) and a low-cost web camera for the acquisition of breast tissue images. The system is automatic, and its control, through a graphical user interface (GUI), saves costs and allows for the subsequent analysis of images using a digital image-processing algorithm. The results obtained allow for the possibility of planning in vivo measurements. In addition, the acquisition of images every 30° around the breast tissue could be used in future research in order to perform a three-dimensional (3D) reconstruction and an analysis of the captures through deep learning techniques. These could be combined with virtual, augmented, or mixed reality environments to predict the position of tumors, increase the likelihood of a correct medical diagnosis, and develop a training system for specialists. Furthermore, the system allows for the possibility to develop analysis of optical characterization for new phantom studies in breast cancer diagnosis through bioimaging techniques.

Fiber-optic pulseoximeter for local oxygen saturation determination using a Monte Carlo multi-layer model for calibration.

BACKGROUND AND OBJECTIVE: Local tissue oxygenation determines the relationship between the supply and the demand for oxygen by the tissue and it is an important indicator of the physiological or pathological condition of the tissue. Moreover, some therapeutic methods strongly depend on the oxygen content of the tissue. In photodynamic therapy, when molecular oxygen is present, the irradiation of the photosensitizer with light triggers the generation of reactive oxygen species that kill the target diseased cells within the treated tissue. To ensure the best possible therapy response, the tissue must be well oxygenated; hence, oxygen concentration measurement becomes a decisive factor. In this work, the design, construction and calibration of a module to locally measure the blood oxygen saturation in tissue is presented. METHODS: The system is built using a red (660-nm) and an infrared (940-nm) light emitting diodes as light sources, a photodiode as a detector, and a homemade handheld fiber optic-based reflectance pulse oximetry sensor. In addition, the developed sensor was modeled by means of multilayered Monte Carlo simulations, to study its behavior when used in different thickness and melanin content skin. RESULTS: From the simulation reflectance values, the oxygen saturation calibration curves considering different melanin concentrations and skin thicknesses were obtained for two different skin models, one comprising three skin layers and the second, assuming seven different layers for the skin. A comparison of the performances of the developed pulse oximeter sensor with a commercial one is also presented. CONCLUSIONS: A new pulseoximeter for the measurement of local oxygenation in tissue was developed. Its calibration strongly depends on the site of measurement due to the influence of tissue thickness, vascularization, and melanin content. A three-layer skin model is proved to be suitable for the calibration of the pulseoximeter in thin and medium thickness skin.