ABSTRACT
Three-dimensional (3D) shape lies at the core of understanding the physical objects that surround us. In the biomedical field, shape analysis has been shown to be powerful in quantifying how anatomy changes with time and disease. The Shape AnaLysis Toolbox (SALT) was created as a vehicle for disseminating advanced shape methodology as an open source, free, and comprehensive software tool. We present new developments in our shape analysis software package, including easy-to-interpret statistical methods to better leverage the quantitative information contained in SALT's shape representations. We also show SlicerPipelines, a module to improve the usability of SALT by facilitating the analysis of large-scale data sets, automating workflows for non-expert users, and allowing the distribution of reproducible workflows.
ABSTRACT
In this paper, we present a deep learning-based method for surface segmentation. This technique consists of acquiring 2D views and extracting features from the surface such as the normal vectors. The rendered images are analyzed with a 2D convolutional neural network, such as a UNET. We test our method in a dental application for the segmentation of dental crowns. The neural network is trained for multi-class segmentation, using image labels as ground truth. A 5-fold cross-validation was performed, and the segmentation task achieved an average Dice of 0.97, sensitivity of 0.98 and precision of 0.98. Our method and algorithms are available as a 3DSlicer extension.
ABSTRACT
This paper proposes an all-numerical robust method to compensate for the chromatic aberrations induced by the optical elements in digital color holographic imaging. It combines a zero-padding algorithm and a convolution approach with adjustable magnification, using a single recording of a reference rectangular grid. Experimental results confirm and validate the proposed approach.
ABSTRACT
This paper proposes a first attempt to visualize and analyze the vibrations induced by a bone-conduction device and propagating at the surface of the skin of a human face. The method is based on a new approach in a so-called quasi-time-averaging regime, resulting in the retrieval of the vibration amplitude and phase from a sequence of digital Fresnel holograms recorded with a high image rate. The design of the algorithm depends on the ratio between the exposure time and the vibration period. The results show the propagation of vibrations at the skin surface, and quantitative analysis is achieved by the proposed approach.
Subject(s)
Elasticity Imaging Techniques/methods , Holography/methods , Refractometry/methods , Signal Processing, Computer-Assisted , Skin Physiological Phenomena/radiation effects , Elastic Modulus/physiology , Humans , Skin/cytology , SoundABSTRACT
This paper presents a detailed analysis of the influence of the pixel dimension in digitally-recorded holograms. The investigation is based on both theoretical and experimental viewpoints for recordings beyond the Shannon limits. After discussing the pixel paradox, the sinc amplitude modulation is experimentally demonstration. The experimental analysis is well correlated to the theoretical basics; in addition, the filling factor of the sensor can be estimated. The analysis of the phase changes of the object show that they can be obtained with a very good contrast and that they are only limited by the decorrelation noise, as when the Shannon conditions are fulfilled.
ABSTRACT
We present a simple scheme to determine the diffusion properties of a thin slab of strongly scattering material by measuring the speckle contrast resulting from the transmission of a femtosecond pulse with controlled bandwidth. In contrast with previous methods, our scheme does not require time measurements nor interferometry. It is well adapted to the characterization of samples for pulse shaping, nonlinear excitation through scattering media, and biological imaging.
