Multispectral Quantum Dots-in-a-Well Infrared Detectors Using Plasmon Assisted Cavities

We present the design, fabrication, and characterization, of multi-spectral quantum dots-in-a-well (DWELL) infrared detectors, by the integration of a surface plasmon assisted resonant cavity with the infrared detector. A square lattice and rectangular lattice cavity, formed by modifying the square lattice have been used in this design. By confining the resonant mode of the cavity to detector active region, the detector responsivity and detectivity have been improved by a factor of 5. A spectral tuning of 5.5 to 7.2 μm has been observed in the peak response of the detectors, by tuning the lattice constant of the cavity. Simulations indicate the presence of two modes of absorption, which have been experimentally verified. The use of a rectangular lattice predicts highly polarization sensitive modes in x- and y-direction, which are observed in fabricated detectors. A peak detectivity of 3.1 x 10^9 cm √(Hz)/W was measured at 77 K. This design offers a cost-effective and simple method of encoding spectral and polarization information, in infrared focal plane arrays

Breast Cancer: Modelling and Detection

This paper reviews a number of the mathematical models used in cancer modelling and then chooses a specific cancer, breast carcinoma, to illustrate how the modelling can be used in aiding detection. We then discuss mathematical models that underpin mammographic image analysis, which complements models of tumour growth and facilitates diagnosis and treatment of cancer. Mammographic images are notoriously difficult to interpret, and we give an overview of the primary image enhancement technologies that have been introduced, before focusing on a more detailed description of some of our own recent work on the use of physics-based modelling in mammography. This theoretical approach to image analysis yields a wealth of information that could be incorporated into the mathematical models, and we conclude by describing how current mathematical models might be enhanced by use of this information, and how these models in turn will help to meet some of the major challenges in cancer detection

CMOS Architectures and circuits for high-speed decision-making from image flows

We present architectures, CMOS circuits and CMOS chips to process image flows at very high speed. This is achieved by exploiting bio-inspiration and performing processing tasks in parallel manner and concurrently with image acquisition. A vision system is presented which makes decisions within sub-msec range. This is very well suited for defense and security applications requiring segmentation and tracking of rapidly moving objects