Deep unsupervised clustering with Gaussian mixture variational autoencoders

We study a variant of the variational autoencoder model with a Gaussian mixture as a prior distribution, with the goal of performing unsupervised clustering through deep generative models. We observe that the standard variational approach in these models is unsuited for unsupervised clustering, and mitigate this problem by leveraging a principled information-theoretic regularisation term known as consistency violation. Adding this term to the standard variational optimisation objective yields networks with both meaningful internal representations and well-defined clusters. We demonstrate the performance of this scheme on synthetic data, MNIST and SVHN, showing that the obtained clusters are distinct, interpretable and result in achieving higher performance on unsupervised clustering classification than previous approaches

Intracortical modulation, and not spinal inhibition, mediates placebo analgesia

Suppression of spinal responses to noxious stimulation has been detected using spinal fMRI during placebo analgesia, which is therefore increasingly considered a phenomenon caused by descending inhibition of spinal activity. However, spinal fMRI is technically challenging and prone to false-positive results. Here we recorded laser-evoked potentials (LEPs) during placebo analgesia in humans. LEPs allow neural activity to be measured directly and with high enough temporal resolution to capture the sequence of cortical areas activated by nociceptive stimuli. If placebo analgesia is mediated by inhibition at spinal level, this would result in a general suppression of LEPs rather than in a selective reduction of their late components. LEPs and subjective pain ratings were obtained in two groups of healthy volunteers - one was conditioned for placebo analgesia while the other served as unconditioned control. Laser stimuli at three suprathreshold energies were delivered to the right hand dorsum. Placebo analgesia was associated with a significant reduction of the amplitude of the late P2 component. In contrast, the early N1 component, reflecting the arrival of the nociceptive input to the primary somatosensory cortex (SI), was only affected by stimulus energy. This selective suppression of late LEPs indicates that placebo analgesia is mediated by direct intracortical modulation rather than inhibition of the nociceptive input at spinal level. The observed cortical modulation occurs after the responses elicited by the nociceptive stimulus in the SI, suggesting that higher order sensory processes are modulated during placebo analgesia

DLTK: State of the Art Reference Implementations for Deep Learning on Medical Images

We present DLTK, a toolkit providing baseline implementations for efficient experimentation with deep learning methods on biomedical images. It builds on top of TensorFlow and its high modularity and easy-to-use examples allow for a low-threshold access to state-of-the-art implementations for typical medical imaging problems. A comparison of DLTK's reference implementations of popular network architectures for image segmentation demonstrates new top performance on the publicly available challenge data "Multi-Atlas Labeling Beyond the Cranial Vault". The average test Dice similarity coefficient of $81.5$ exceeds the previously best performing CNN ($75.7$) and the accuracy of the challenge winning method ($79.0$)

Image-level harmonization of multi-site data using image-and-spatial transformer networks

We investigate the use of image-and-spatial transformer networks (ISTNs) to tackle domain shift in multi-site medical imaging data. Commonly, domain adaptation (DA) is performed with little regard for explainability of the inter-domain transformation and is often conducted at the feature-level in the latent space. We employ ISTNs for DA at the image-level which constrains transformations to explainable appearance and shape changes. As proof-of-concept we demonstrate that ISTNs can be trained adversarially on a classification problem with simulated 2D data. For real-data validation, we construct two 3D brain MRI datasets from the Cam-CAN and UK Biobank studies to investigate domain shift due to acquisition and population differences. We show that age regression and sex classification models trained on ISTN output improve generalization when training on data from one and testing on the other site

Image registration via stochastic gradient markov chain monte carlo

We develop a fully Bayesian framework for non-rigid registration of three-dimensional medical images, with a focus on uncertainty quantification. Probabilistic registration of large images along with calibrated uncertainty estimates is difficult for both computational and modelling reasons. To address the computational issues, we explore connections between the Markov chain Monte Carlo by backprop and the variational inference by backprop frameworks in order to efficiently draw thousands of samples from the posterior distribution. Regarding the modelling issues, we carefully design a Bayesian model for registration to overcome the existing barriers when using a dense, high-dimensional, and diffeomorphic parameterisation of the transformation. This results in improved calibration of uncertainty estimates

Regulator Vulnerabilities to Political Pressure and Political Tie Intensity: The Moderating Effects of Regulatory and Political Distance

This study applies the institution-based view and neo-institutional theory in addressing how managerial perceptions of regulator vulnerabilities to political pressure, and institutional distance, influence intensification of political ties. Our analysis of 181 wholly owned foreign subsidiary (WOFSs) operating in the Philippines suggests that managerial perceptions of regulator vulnerability to political pressures positively enhance the intensification of political ties. Our results also reveal that regulatory distance and, more importantly, the simultaneous presence of political and regulatory distance diminish the positive relationship between managerial perceptions of regulator vulnerability to political pressures and a WOFS’s propensity to enhance the intensification of political ties. Managerial implications and future research directions are discusse

RapidArc radiotherapy planning for prostate cancer: Single-arc and double-arc techniques vs. intensity-modulated radiotherapy

RapidArc is a novel technique using arc radiotherapy aiming to achieve intensity-modulated radiotherapy (IMRT)-quality radiotherapy plans with shorter treatment time. This study compared the dosimetric quality and treatment efficiency of single-arc (SA) vs. double-arc (DA) and IMRT in the treatment of prostate cancer. Fourteen patients were included in the analysis. The planning target volume (PTV), which contained the prostate gland and proximal seminal vesicles, received 76 Gy in 38 fractions. Seven-field IMRT, SA, and DA plans were generated for each patient. Dosimetric quality in terms of the minimum PTV dose, PTV hotspot, inhomogeneity, and conformity index; and sparing of rectum, bladder, and femoral heads as measured by V70, V-40, and V20 (% of volume receiving >70 Gy, 40 Gy, and 20 Gy, respectively), treatment efficiency as assessed by monitor units (MU) and treatment time were compared. All plan objectives were met satisfactorily by all techniques. DA achieved the best dosimetric quality with the highest minimum PTV dose, lowest hotspot, and the best homogeneity and conformity. It was also more efficient than IMRT. SA achieved the highest treatment efficiency with the lowest MU and shortest treatment time. The mean treatment time for a 2-Gy fraction was 4.80 min, 2.78 min, and 1.30 min for IMRT, DA, and SA, respectively. However, SA also resulted in the highest rectal dose. DA could improve target volume coverage and reduce treatment time and MU while maintaining equivalent normal tissue sparing when compared with IMRT. SA achieved the greatest treatment efficiency but with the highest rectal dose, which was nonetheless within tolerable limits. For busy units with high patient throughput, SA could be an acceptable option. © 2012 American Association of Medical Dosimetrists.link_to_subscribed_fulltex