*J Med Imaging (Bellingham) ; 4(1): 014501, 2017 Jan.*

##### RESUMO

Quantitative cephalometry plays an essential role in clinical diagnosis, treatment, and surgery. Development of fully automated techniques for these procedures is important to enable consistently accurate computerized analyses. We study the application of deep convolutional neural networks (CNNs) for fully automated quantitative cephalometry for the first time. The proposed framework utilizes CNNs for detection of landmarks that describe the anatomy of the depicted patient and yield quantitative estimation of pathologies in the jaws and skull base regions. We use a publicly available cephalometric x-ray image dataset to train CNNs for recognition of landmark appearance patterns. CNNs are trained to output probabilistic estimations of different landmark locations, which are combined using a shape-based model. We evaluate the overall framework on the test set and compare with other proposed techniques. We use the estimated landmark locations to assess anatomically relevant measurements and classify them into different anatomical types. Overall, our results demonstrate high anatomical landmark detection accuracy ([Formula: see text] to 2% higher success detection rate for a 2-mm range compared with the top benchmarks in the literature) and high anatomical type classification accuracy ([Formula: see text] average classification accuracy for test set). We demonstrate that CNNs, which merely input raw image patches, are promising for accurate quantitative cephalometry.

*Opt Lett ; 41(18): 4265-8, 2016 Sep 15.*

##### RESUMO

Mode-division multiplexing (MDM) can increase the capacity of direct-detection short-reach systems in proportion to the number of modes employed. MDM requires compensation of modal crosstalk at a transmitter or receiver by the multi-input multi-output (MIMO) signal processing. We show that the channel estimation required for the MIMO processing in a basis of modes can be expressed as a phase retrieval problem. We propose three techniques for the estimation: sparse training sequences, convex optimization (CO) and alternating minimization. We demonstrate the superior performance of the CO technique.

*Opt Lett ; 39(11): 3258-61, 2014 Jun 01.*

##### RESUMO

The capacity of mode-division multiplexing (MDM) systems is limited, for a given outage probability, by mode-dependent loss (MDL) and gain. Modal degrees of freedom may be exploited to increase transmission rate (multiplexing gain) or lower outage probability (diversity gain), but there is a fundamental tradeoff between the achievable multiplexing and diversity gains. In this Letter, we present the diversity-multiplexing tradeoff in MDM systems for the first time, studying the impact of signal-to-noise ratio, MDL, and frequency diversity order on the tradeoff in the strong-mode-coupling regime.

*Opt Express ; 22(7): 8798-812, 2014 Apr 07.*

##### RESUMO

In this paper, we examine the performance of several modulation formats in more than four dimensions for coherent optical communications systems. We compare two high-dimensional modulation design methodologies based on spherical cutting of lattices and block coding of a 'base constellation' of binary phase shift keying (BPSK) on each dimension. The performances of modulation formats generated with these methodologies is analyzed in the asymptotic signal-to-noise ratio regime and for an additive white Gaussian noise (AWGN) channel. We then study the application of both types of high-dimensional modulation formats to standard single-mode fiber (SSMF) transmission systems. For modulation with spectral efficiencies comparable to dual-polarization (DP-) BPSK, polarization-switched quaternary phase shift keying (PS-QPSK) and DP-QPSK, we demonstrate SNR gains of up to 3 dB, 0.9 dB and 1 dB respectively, at a BER of 10(-3).

*Opt Express ; 22(24): 29868-87, 2014 Dec 01.*

##### RESUMO

As the bit rates of routed data streams exceed the throughput of single wavelength-division multiplexing channels, spectral and spatial traffic aggregation become essential for optical network scaling. These aggregation techniques reduce network routing complexity by increasing spectral efficiency to decrease the number of fibers, and by increasing switching granularity to decrease the number of switching components. Spectral aggregation yields a modest decrease in the number of fibers but a substantial decrease in the number of switching components. Spatial aggregation yields a substantial decrease in both the number of fibers and the number of switching components. To quantify routing complexity reduction, we analyze the number of multi-cast and wavelength-selective switches required in a colorless, directionless and contentionless reconfigurable optical add-drop multiplexer architecture. Traffic aggregation has two potential drawbacks: reduced routing power and increased switching component size.

##### Assuntos

Fenômenos Ópticos , Dispositivos Ópticos , Fibras Ópticas , Processamento de Sinais Assistido por Computador , Análise Espectral*Opt Lett ; 37(1): 103-5, 2012 Jan 01.*

##### RESUMO

Fresnel integrals corresponding to different distances can be interpreted as scaled fractional Fourier transformations observed on spherical reference surfaces. Transverse samples can be taken on these surfaces with separation that increases with propagation distance. Here, we are concerned with the separation of the spherical reference surfaces along the longitudinal direction. We show that these surfaces should be equally spaced with respect to the fractional Fourier transform order, rather than being equally spaced with respect to the distance of propagation along the optical axis. The spacing should be of the order of the reciprocal of the space-bandwidth product of the signals. The space-dependent longitudinal and transverse spacings define a grid that reflects the structure of Fresnel diffraction.

*Opt Lett ; 36(13): 2524-6, 2011 Jul 01.*

##### RESUMO

Fresnel integrals corresponding to different distances can be interpreted as scaled fractional Fourier transformations observed on spherical reference surfaces. We show that by judiciously choosing sample points on these curved reference surfaces, it is possible to represent the diffracted signals in a nonredundant manner. The change in sample spacing with distance reflects the structure of Fresnel diffraction. This sampling grid also provides a simple and robust basis for accurate and efficient computation, which naturally handles the challenges of sampling chirplike kernels.