This paper presents a novel technique to correct for bias in a classical estimator using a learning approach. We apply a learned bias correction to a lidar-only motion estimation pipeline. Our technique trains a Gaussian process (GP) regression model using data with ground truth. The inputs to the model are high-level features derived from the geometry of the point-clouds, and the outputs are t...

Introduction: Functional MRI methods have been used to study sensorimotor processing in the Spinal cord. However, these techniques confront unwanted contributions to the measured signal from the physiological fluctuations. For the spinal cord imaging, most of the challenges are consequences of cardiac and respiratory movement artifacts that are considered as significant sources of noise, especi...

abstract background: correction of severe kyphosis is a challenging operation in spinal surgery. a two stage operation has been commonly used: anterior release and decompression followed by posterior correction and fusion. we describe the posterior vertebral osteotomy technique for correction of severe and rigid kyphosis through posterior-only approach. methods: twelve patients (six male and si...

purpose: to report a case who had undergone lasik in his right eye and prk in the fellow eye for correction of equivalent myopia but developed progressive post-operative keratectasia only in the right eye. patient and findings: a 30-year-old man had undergone lasik in right eye 3 years ago for correction of refractive error of -1.75  -1.50@48° and prk in left eye 2 years ago for correction of r...

in present pet/ct scanners, pet attenuation correction is performed by relying on the information given by ct scan. in the ct-based attenuation correction methods, dual-energy technique (dect) is the most accurate approach, which has been limited due to the increasing patient dose. in this feasibility study, we have introduced a new method that can implement dual-energy technique with only a si...

We study the problem of k-visibility in the memoryconstrained model. In this model, the input resides in a randomly accessible read-only memory of O(n) words with O(log n) bits each. An algorithm can read and write O(s) additional words of workspace during its execution, and it writes its output to write-only memory. In a given polygon P , for a given point q ∈ P , we say a point p is inside th...