Artificial Intelligence

Contains research objectives and reports on eight research projects.Computation Center, M.I.T

Nonlinear Markov Random Fields Learned via Backpropagation

Although convolutional neural networks (CNNs) currently dominate competitions on image segmentation, for neuroimaging analysis tasks, more classical generative approaches based on mixture models are still used in practice to parcellate brains. To bridge the gap between the two, in this paper we propose a marriage between a probabilistic generative model, which has been shown to be robust to variability among magnetic resonance (MR) images acquired via different imaging protocols, and a CNN. The link is in the prior distribution over the unknown tissue classes, which are classically modelled using a Markov random field. In this work we model the interactions among neighbouring pixels by a type of recurrent CNN, which can encode more complex spatial interactions. We validate our proposed model on publicly available MR data, from different centres, and show that it generalises across imaging protocols. This result demonstrates a successful and principled inclusion of a CNN in a generative model, which in turn could be adapted by any probabilistic generative approach for image segmentation.Comment: Accepted for the international conference on Information Processing in Medical Imaging (IPMI) 2019, camera ready versio

Methods for specifying the target difference in a randomised controlled trial : the Difference ELicitation in TriAls (DELTA) systematic review

Peer reviewedPublisher PD

Advances in hormone replacement therapy: making the menopause manageable

The importance of the results of some large, randomized controlled trials (RCTs) on Hormone Replacement Therapy (HRT) has modified the risk/benefit perception of HRT. Recent literature review supports a different management

3D Volume Reconstruction by Serially Acquired 2D Slices Using a Distance Transform-Based Global Cost Function

Abstract. An accurate, computationally eÆcient and fully-automated algorithm for the alignment of 2D serially acquired sections forming a 3D volume is presented. The method accounts for the main shortcomings of 3D image alignment: corrupted data (cuts and tears), dissimilarities or discontinuities between slices, missing slices. The approach relies on the optimization of a global energy function, based on the object shape, measuring the similarity between a slice and its neighborhood in the 3D volume. Slice similarity is computed using the distance transform measure in both directions. No particular direction is privileged in the method avoiding global osets, biases in the estimation and error prop-agation. The method was evaluated on real images (medical, biological and other CT scanned 3D data) and the experimental results demon-strated the method's accuracy as reconstuction errors are less than 1 degree in rotation and less than 1 pixel in translation.

The relative efficacy of nine osteoporosis medications for reducing the rate of fractures in post-menopausal women

<p>Abstract</p> <p>Background</p> <p>In the absence of head-to-head trials, indirect comparisons of randomized placebo-controlled trials may provide a viable option to assess relative efficacy. The purpose was to estimate the relative efficacy of reduction of fractures in post-menopausal women, and to assess robustness of the results.</p> <p>Methods</p> <p>A systematic literature review of multiple databases identified randomized placebo-controlled trials with nine drugs for post-menopausal women. Odds ratio and 95% credibility intervals for the rates of hip, non-vertebral, vertebral, and wrist fractures for each drug and between drugs were derived using a Bayesian approach. A drug was ranked as the most efficacious if it had the highest posterior odds ratio, or had the highest effect size.</p> <p>Results</p> <p>30 studies including 59,209 patients reported fracture rates for nine drugs: alendronate (6 studies), denosumab (1 study), etidronate (8 studies), ibandronate (4 studies), raloxifene (1 study), risedronate (7 studies), strontium (2 study), teriparatide (1 study), and zoledronic acid (1 study). The drugs with the highest probability of reducing non-vertebral fractures was etidronate and teriparatide while the drugs with the highest probability of reducing vertebral, hip or wrist fractures were teriparatide, zoledronic acid and denosumab. The drugs with the largest effect size for vertebral fractures were zoledronic acid, teriparatide and denosumab, while the drugs with the highest effect size for non-vertebral, hip or wrist fractures were alendronate or risedronate. Estimates were consistent between Bayesian and classical approaches.</p> <p>Conclusion</p> <p>Teriparatide, zoledronic acid and denosumab have the highest probabilities of being most efficacious for non-vertebral and vertebral fractures, and having the greatest effect sizes. The estimates from indirect comparisons were robust to differences in methodology.</p

Linear Collider Physics Resource Book for Snowmass 2001, 3: Studies of Exotic and Standard Model Physics

This Resource Book reviews the physics opportunities of a next-generation e+e- linear collider and discusses options for the experimental program. Part 3 reviews the possible experiments on that can be done at a linear collider on strongly coupled electroweak symmetry breaking, exotic particles, and extra dimensions, and on the top quark, QCD, and two-photon physics. It also discusses the improved precision electroweak measurements that this collider will make available.This Resource Book reviews the physics opportunities of a next-generation e+e- linear collider and discusses options for the experimental program. Part 3 reviews the possible experiments on that can be done at a linear collider on strongly coupled electroweak symmetry breaking, exotic particles, and extra dimensions, and on the top quark, QCD, and two-photon physics. It also discusses the improved precision electroweak measurements that this collider will make available