Learning Deep Similarity Metric for 3D MR-TRUS Registration

Purpose: The fusion of transrectal ultrasound (TRUS) and magnetic resonance (MR) images for guiding targeted prostate biopsy has significantly improved the biopsy yield of aggressive cancers. A key component of MR-TRUS fusion is image registration. However, it is very challenging to obtain a robust automatic MR-TRUS registration due to the large appearance difference between the two imaging modalities. The work presented in this paper aims to tackle this problem by addressing two challenges: (i) the definition of a suitable similarity metric and (ii) the determination of a suitable optimization strategy. Methods: This work proposes the use of a deep convolutional neural network to learn a similarity metric for MR-TRUS registration. We also use a composite optimization strategy that explores the solution space in order to search for a suitable initialization for the second-order optimization of the learned metric. Further, a multi-pass approach is used in order to smooth the metric for optimization. Results: The learned similarity metric outperforms the classical mutual information and also the state-of-the-art MIND feature based methods. The results indicate that the overall registration framework has a large capture range. The proposed deep similarity metric based approach obtained a mean TRE of 3.86mm (with an initial TRE of 16mm) for this challenging problem. Conclusion: A similarity metric that is learned using a deep neural network can be used to assess the quality of any given image registration and can be used in conjunction with the aforementioned optimization framework to perform automatic registration that is robust to poor initialization.Comment: To appear on IJCAR

NICI: combining coronagraphy, ADI, and SDI

The Near-Infrared Coronagraphic Imager (NICI) is a high-contrast AO imager at the Gemini South telescope. The camera includes a coronagraphic mask and dual channel imaging for Spectral Differential Imaging (SDI). The instrument can also be used in a fixed Cassegrain Rotator mode for Angular Differential Imaging (ADI). While coronagraphy, SDI, and ADI have been applied before in direct imaging searches for exoplanets. NICI represents the first time that these 3 techniques can be combined. We present preliminary NICI commissioning data using these techniques and show that combining SDI and ADI results in significant gains.Comment: Proc. SPIE, Vol. 7014, 70141Z (2008

A quantum volume hologram

We propose a new scheme for parallel spatially multimode quantum memory for light. The scheme is based on counter-propagating quantum signal wave and strong classical reference wave, like in a classical volume hologram, and therefore can be called a quantum volume hologram. The medium for the hologram consists of a spatially extended ensemble of atoms placed in a magnetic field. The write-in and read-out of this quantum hologram is as simple as that of its classical counterpart and consists of a single pass illumination. In addition we show that the present scheme for a quantum hologram is less sensitive to diffraction and therefore is capable of achieving higher density of storage of spatial modes as compared to previous proposals. A quantum hologram capable of storing entangled images can become an important ingredient in quantum information processing and quantum imaging.Comment: 8 pages, 2 figure