DynAMITe: A prototype large area CMOS APS for breast cancer diagnosis using x-ray diffraction measurements

X-ray diffraction studies are used to identify specific materials. Several laboratory-based x-ray diffraction studies were made for breast cancer diagnosis. Ideally a large area, low noise, linear and wide dynamic range digital x-ray detector is required to perform x-ray diffraction measurements. Recently, digital detectors based on Complementary Metal-Oxide- Semiconductor (CMOS) Active Pixel Sensor (APS) technology have been used in x-ray diffraction studies. Two APS detectors, namely Vanilla and Large Area Sensor (LAS), were developed by the Multidimensional Integrated Intelligent Imaging (MI-3) consortium to cover a range of scientific applications including x-ray diffraction. The MI-3 Plus consortium developed a novel large area APS, named as Dynamically Adjustable Medical Imaging Technology (DynAMITe), to combine the key characteristics of Vanilla and LAS with a number of extra features. The active area (12.8 � 13.1 cm 2) of DynaMITe offers the ability of angle dispersive x-ray diffraction (ADXRD). The current study demonstrates the feasibility of using DynaMITe for breast cancer diagnosis by identifying six breast-equivalent plastics. Further work will be done to optimize the system in order to perform ADXRD for identification of suspicious areas of breast tissue following a conventional mammogram taken with the same sensor. © 2012 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).</p

DynAMITe: a prototype large area CMOS APS for breast cancer diagnosis using x-ray diffraction measurements

X-ray diffraction studies are used to identify specific materials. Several laboratory-based x-ray diffraction studies were made for breast cancer diagnosis. Ideally a large area, low noise, linear and wide dynamic range digital x-ray detector is required to perform x-ray diffraction measurements. Recently, digital detectors based on Complementary Metal-Oxide- Semiconductor (CMOS) Active Pixel Sensor (APS) technology have been used in x-ray diffraction studies. Two APS detectors, namely Vanilla and Large Area Sensor (LAS), were developed by the Multidimensional Integrated Intelligent Imaging (MI-3) consortium to cover a range of scientific applications including x-ray diffraction. The MI-3 Plus consortium developed a novel large area APS, named as Dynamically Adjustable Medical Imaging Technology (DynAMITe), to combine the key characteristics of Vanilla and LAS with a number of extra features. The active area (12.8 × 13.1 cm 2) of DynaMITe offers the ability of angle dispersive x-ray diffraction (ADXRD). The current study demonstrates the feasibility of using DynaMITe for breast cancer diagnosis by identifying six breast-equivalent plastics. Further work will be done to optimize the system in order to perform ADXRD for identification of suspicious areas of breast tissue following a conventional mammogram taken with the same sensor. © 2012 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).</p

Classification of audio signals using statistical features on time and wavelet transform domains

This paper presents a study on musical signal classification, using wavelet transform analysis in conjunction with statistical pattern recognition techniques. A comparative evaluation between different wavelet analysis architectures in terms of their classification ability, as well as between different classifiers is carried out. We seek to establish which statistical measures clearly distinguish between the three different musical styles of rock, piano, and jazz. Our preliminary results suggest that the features collected by the adaptive splitting wavelet transform technique performed better compared to the other wavelet based techniques, achieving overall classification accuracy of 91.67, using either the Minimum Distance Classifier or the Least Squares Minimum Distance Classifier. Such a system can play a useful part in multimedia applications which require content based search, classification, and retrieval of audio signals, as defined in MPEG-7.</p