Evaluation of a novel wafer-scale CMOS APS X-ray detector for use in mammography

The most important factors that affect the image quality are contrast, spatial resolution and noise. These factors and their relationship are quantitatively described by the Contrast-to-Noise Ratio (CNR), Signal-to-Noise Ratio (SNR), Modulation Transfer Function (MTF), Noise Power Spectrum (NPS) and Detective Quantum Efficiency (DQE) parameters. The combination of SNR, MTF and NPS determines the DQE, which represents the ability to visualize object details of a certain size and contrast at a given dose. In this study the performance of a novel large area Complementary Metal-Oxide-Semiconductor (CMOS) Active Pixel Sensor (APS) X-ray detector, called DynAMITe (Dynamic range Adjustable for Medical Imaging Technology), was investigated and compared to other three digital mammography systems (namely a) Large Area Sensor (LAS), b) Hamamatsu C9732DK, and c) Anrad SMAM), in terms of physical characteristics and evaluation of the image quality. DynAMITe detector consists of two geometrically superimposed grids: a) 2560 � 2624 pixels at 50 μm pitch, named Sub-Pixels (SP camera) and b) 1280 � 1312 pixels at 100 μm pitch, named Pixels (P camera). The X-ray performance evaluation of DynAMITe SP detector demonstrated high DQE results (0.58 to 0.64 at 0.5 lp/mm). Image simulation based on the X-ray performance of the detectors was used to predict and compare the mammographic image quality using ideal software phantoms: a) one representing two three dimensional (3-D) breasts of various thickness and glandularity to estimate the CNR between simulated microcalcifications and the background, and b) the CDMAM 3.4 test tool for a contrast-detail analysis of small thickness and low contrast objects. The results show that DynAMITe SP detector results in high CNR and contrast-detail performance. © 2012 IEEE.</p

Evaluation of a novel wafer-scale CMOS APS X-ray detector for use in mammography

The most important factors that affect the image quality are contrast, spatial resolution and noise. These factors and their relationship are quantitatively described by the Contrast-to-Noise Ratio (CNR), Signal-to-Noise Ratio (SNR), Modulation Transfer Function (MTF), Noise Power Spectrum (NPS) and Detective Quantum Efficiency (DQE) parameters. The combination of SNR, MTF and NPS determines the DQE, which represents the ability to visualize object details of a certain size and contrast at a given dose. In this study the performance of a novel large area Complementary Metal-Oxide-Semiconductor (CMOS) Active Pixel Sensor (APS) X-ray detector, called DynAMITe (Dynamic range Adjustable for Medical Imaging Technology), was investigated and compared to other three digital mammography systems (namely a) Large Area Sensor (LAS), b) Hamamatsu C9732DK, and c) Anrad SMAM), in terms of physical characteristics and evaluation of the image quality. DynAMITe detector consists of two geometrically superimposed grids: a) 2560 � 2624 pixels at 50 μm pitch, named Sub-Pixels (SP camera) and b) 1280 � 1312 pixels at 100 μm pitch, named Pixels (P camera). The X-ray performance evaluation of DynAMITe SP detector demonstrated high DQE results (0.58 to 0.64 at 0.5 lp/mm). Image simulation based on the X-ray performance of the detectors was used to predict and compare the mammographic image quality using ideal software phantoms: a) one representing two three dimensional (3-D) breasts of various thickness and glandularity to estimate the CNR between simulated microcalcifications and the background, and b) the CDMAM 3.4 test tool for a contrast-detail analysis of small thickness and low contrast objects. The results show that DynAMITe SP detector results in high CNR and contrast-detail performance. © 2012 IEEE.</p

The multidimensional integrated intelligent imaging project (MI-3)

MI-3 is a consortium of 11 universities and research laboratories whose mission is to develop complementary metal-oxide semiconductor (CMOS) active pixel sensors (APS) and to apply these sensors to a range of imaging challenges. A range of sensors has been developed: On-Pixel Intelligent CMOS (OPIC)—designed for in-pixel intelligence; FPN—designed to develop novel techniques for reducing fixed pattern noise; HDR—designed to develop novel techniques for increasing dynamic range; Vanilla/PEAPS—with digital and analogue modes and regions of interest, which has also been back-thinned; Large Area Sensor (LAS)—a novel, stitched LAS; and eLeNA—which develops a range of low noise pixels. Applications being developed include autoradiography, a gamma camera system, radiotherapy verification, tissue diffraction imaging, X-ray phase-contrast imaging, DNA sequencing and electron microscopy.</p

The multidimensional integrated intelligent imaging project (MI-3)

MI-3 is a consortium of 11 universities and research laboratories whose mission is to develop complementary metal-oxide semiconductor (CMOS) active pixel sensors (APS) and to apply these sensors to a range of imaging challenges. A range of sensors has been developed: On-Pixel Intelligent CMOS (OPIC)—designed for in-pixel intelligence; FPN—designed to develop novel techniques for reducing fixed pattern noise; HDR—designed to develop novel techniques for increasing dynamic range; Vanilla/PEAPS—with digital and analogue modes and regions of interest, which has also been back-thinned; Large Area Sensor (LAS)—a novel, stitched LAS; and eLeNA—which develops a range of low noise pixels. Applications being developed include autoradiography, a gamma camera system, radiotherapy verification, tissue diffraction imaging, X-ray phase-contrast imaging, DNA sequencing and electron microscopy.</p