Advances in Breast Thermography

Thermography‐based breast cancer screening has several advantages as it is non-contact, non-invasive and safe. Many clinical trials have shown its effectiveness to detect cancer earlier than any other modality. Historically, thermography has only been used as an adjunct modality due to the high expertise required for manual interpretation of the thermal images and high false‐positive rates otherwise found in general use. Recent developments in thermal sensors, image capture protocols and computer‐aided software diagnostics are showing great promise in making this modality a mainstream cancer screening method. This chapter describes some of these advances in breast thermography and computer‐aided diagnostics that are poised to improve the quality of cancer care

Prototypes for Content-Based Image Retrieval in Clinical Practice

Content-based image retrieval (CBIR) has been proposed as key technology for computer-aided diagnostics (CAD). This paper reviews the state of the art and future challenges in CBIR for CAD applied to clinical practice

Design of a Solid Freeform Fabrication Diamond Reactor

Solid Freeform Fabrication (SFF) has progressed from the visualization aided stage of computer aided designs (CAD) to rapid prototyping of structural parts. Among the promising techniques for producing structural prototypes is the technology ofchemical vapor deposition (CVD) ofpolycrystalline diamond. This paper discusses the thermodynamic and kinetic theories that suggest that structural diamond may be rapidly deposited at rates approaching 1 mmJhr from the vapor phase at metastable thermodynamic conditions. The design of a reactor that will produce structural diamond prototypes is discussed. This reactor combines downstream microwave plasma enhanced chemical vapor deposition (DMWPECVD) with a scanned CO2 laser that locally heats the substrate to diamond deposition temperatures. The input:Fases are H2, 02' CH4, and Ar. The operating pressure range of the reactor is 1 x 10- to 7 x 102 Torr. The reactor is designed for in situ determination of deposit thickness while deposition occurs as well as having the capacity of fitting on an existing resonance enhanced multiphoton ionization time of flight mass spectroscopy (REMPITOFMS) apparatus that will allow for plasma diagnostics immediately above the heated substrate. Plasma diagnostics will be employed to determine the active metastable species that results in diamond deposition so that optimization can be made ofthe operating parameters to maximize diamond selectivity and deposition rate.Mechanical Engineerin

Object oriented fault diagnosis system for space shuttle main engine redlines

A great deal of attention has recently been given to Artificial Intelligence research in the area of computer aided diagnostics. Due to the dynamic and complex nature of space shuttle red-line parameters, a research effort is under way to develop a real time diagnostic tool that will employ historical and engineering rulebases as well as a sensor validity checking. The capability of AI software development tools (KEE and G2) will be explored by applying object oriented programming techniques in accomplishing the diagnostic evaluation

Mathematical Modelling and Computer Simulation Assist in Designing Non-traditional Types of Precipitators and Separators

The article deals with the application of the method for mathematical modeling and simulation at solving some issues in the area of electrostatic technology. It focuses on the processes in electrostatic separation and precipitation. Computer simulation is highly required for equipment design and for their diagnostics in critical operating states using theoretical calculations and experimental data evaluation. The presented computer models may be applied both by project and design engineers using the most advanced computer-aided design of electrostatic technologies

Recent advancement in Disease Diagnostic using machine learning: Systematic survey of decades, comparisons, and challenges

Computer-aided diagnosis (CAD), a vibrant medical imaging research field, is expanding quickly. Because errors in medical diagnostic systems might lead to seriously misleading medical treatments, major efforts have been made in recent years to improve computer-aided diagnostics applications. The use of machine learning in computer-aided diagnosis is crucial. A simple equation may result in a false indication of items like organs. Therefore, learning from examples is a vital component of pattern recognition. Pattern recognition and machine learning in the biomedical area promise to increase the precision of disease detection and diagnosis. They also support the decision-making process's objectivity. Machine learning provides a practical method for creating elegant and autonomous algorithms to analyze high-dimensional and multimodal bio-medical data. This review article examines machine-learning algorithms for detecting diseases, including hepatitis, diabetes, liver disease, dengue fever, and heart disease. It draws attention to the collection of machine learning techniques and algorithms employed in studying conditions and the ensuing decision-making process

Computer-aided technologies in diagnostics and therapy of impacted teeth

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Computer Aided Multi-Parameter Extraction System to Aid Early Detection of Skin Cancer Melanoma

Melanoma is the most widely occurring and life threatening form of skin cancer. Early detection of in situ melanoma has challenged researchers for many decades now. Currently there exists no computer aided mechanisms to accurately detect early melanoma. T he currently existing computer aided diagnostics mechanisms are capable of melanoma classification and are unable to detect in situ melanoma. This paper introduces a Multi Parameter Extraction and Classification System ( 푀푀푀푀푀 ) to aid early detection o f skin cancer melanoma. The 푀푀푀푀푀 defines the skin lesion images in terms of characteristic parameters which are further used for classification. In this paper the extraction of 21 parameters is achieved using a six phase approach. The parameters extr acted are analyzed using statistical methods. It is clear from the results obtained that no single parameter can affirm the detection of in situ melanoma, hence an advanced analysis mechanisms considering all the parameters need to be adopted to effective ly detect melanoma in its initial stages

System for Monitoring Environmental Parameters in a Hospital Facility

The paper presents a system for managing and monitoring environ- mental parameters in hospital facilities. It relies on existing data collected with a CAFM (Computer Aided Facility Management) system and allows granted users (such as CEO or Energy Manager) to monitor the ongoing energy consumption of a given activity area (Operating Rooms, Diagnostics, Intensive Care Units, Wards) in relation to the compliance to relevant threshold parameters. The sys- tem easily outputs aggregated data via PDF reporting