A self-supervised learning strategy for postoperative brain cavity segmentation simulating resections

PURPOSE: Accurate segmentation of brain resection cavities (RCs) aids in postoperative analysis and determining follow-up treatment. Convolutional neural networks (CNNs) are the state-of-the-art image segmentation technique, but require large annotated datasets for training. Annotation of 3D medical images is time-consuming, requires highly trained raters and may suffer from high inter-rater variability. Self-supervised learning strategies can leverage unlabeled data for training. METHODS: We developed an algorithm to simulate resections from preoperative magnetic resonance images (MRIs). We performed self-supervised training of a 3D CNN for RC segmentation using our simulation method. We curated EPISURG, a dataset comprising 430 postoperative and 268 preoperative MRIs from 430 refractory epilepsy patients who underwent resective neurosurgery. We fine-tuned our model on three small annotated datasets from different institutions and on the annotated images in EPISURG, comprising 20, 33, 19 and 133 subjects. RESULTS: The model trained on data with simulated resections obtained median (interquartile range) Dice score coefficients (DSCs) of 81.7 (16.4), 82.4 (36.4), 74.9 (24.2) and 80.5 (18.7) for each of the four datasets. After fine-tuning, DSCs were 89.2 (13.3), 84.1 (19.8), 80.2 (20.1) and 85.2 (10.8). For comparison, inter-rater agreement between human annotators from our previous study was 84.0 (9.9). CONCLUSION: We present a self-supervised learning strategy for 3D CNNs using simulated RCs to accurately segment real RCs on postoperative MRI. Our method generalizes well to data from different institutions, pathologies and modalities. Source code, segmentation models and the EPISURG dataset are available at https://github.com/fepegar/resseg-ijcars

Microwave studies of the fractional Josephson effect in HgTe-based Josephson junctions

The rise of topological phases of matter is strongly connected to their potential to host Majorana bound states, a powerful ingredient in the search for a robust, topologically protected, quantum information processing. In order to produce such states, a method of choice is to induce superconductivity in topological insulators. The engineering of the interplay between superconductivity and the electronic properties of a topological insulator is a challenging task and it is consequently very important to understand the physics of simple superconducting devices such as Josephson junctions, in which new topological properties are expected to emerge. In this article, we review recent experiments investigating topological superconductivity in topological insulators, using microwave excitation and detection techniques. More precisely, we have fabricated and studied topological Josephson junctions made of HgTe weak links in contact with two Al or Nb contacts. In such devices, we have observed two signatures of the fractional Josephson effect, which is expected to emerge from topologically-protected gapless Andreev bound states. We first recall the theoretical background on topological Josephson junctions, then move to the experimental observations. Then, we assess the topological origin of the observed features and conclude with an outlook towards more advanced microwave spectroscopy experiments, currently under development.Comment: Lectures given at the San Sebastian Topological Matter School 2017, published in "Topological Matter. Springer Series in Solid-State Sciences, vol 190. Springer

Deformation Aware Augmented Reality for Craniotomy using 3D/2D Non-rigid Registration of Cortical Vessels

International audienceIntra-operative brain shift is a well-known phenomenon that describes non-rigid deformation of brain tissues due to gravity and loss of cerebrospinal fluid among other phenomena. This has a negative influence on surgical outcome that is often based on pre-operative planning where the brain shift is not considered. We present a novel brain-shift aware Augmented Reality method to align pre-operative 3D data onto the deformed brain surface viewed through a surgical microscope. We formulate our non-rigid registration as a Shape-from-Template problem. A pre-operative 3D wire-like deformable model is registered onto a single 2D image of the cortical vessels, which is automatically segmented. This 3D/2D registration drives the underlying brain structures, such as tumors, and compensates for the brain shift in sub-cortical regions. We evaluated our approach on simulated and real data composed of 6 patients. It achieved good quantitative and qualitative results making it suitable for neurosurgical guidance

Legal Facts and Reasons for Action: Between Deflationary and Robust Conceptions of Law’s Reason-Giving Capacity

This chapter considers whether legal requirements can constitute reasons for action independently of the merits of the requirement at hand. While jurisprudential opinion on this question is far from uniform, sceptical views are becoming increasingly dominant. Such views typically contend that, while the law can be indicative of pre-existing reasons, or can trigger pre-existing reasons into operation, it cannot constitute new reasons. This chapter offers support to a somewhat less sceptical position, according to which the fact that a legal requirement has been issued can be a reason for action, yet one that is underpinned by bedrock values which law is apt to serve. Notions discussed here include a value-based conception of reasons as facts ; a distinction between complete and incomplete reasons ; and David Enoch’s idea of triggering reason-giving. Following a discussion of criticism against the view adopted here, the chapter concludes by considering some more ‘robust’ conceptions of law’s reason-giving capacity

Grains from ear to ear: the morphology of spelt and free-threshing wheat from Roman Mursa (Osijek), Croatia

Cereals were a significant part of the Roman diet, yet knowledge about their cultivation, distribution and consumption in certain regions is particularly lacking. In Europe, studies generally suggest that from the Iron Age to the Roman period there was a reduction in barley cultivation, an increase in spelt over emmer, a preference for free-threshing wheat over glume wheats, as well as the increased cultivation of rye and oats. Up till now, there was little evidence on crop cultivation in Croatia, but the discovery of around 24,000 cereal grains from the oven of a 2nd-4th c. AD Roman villa in the modern town of Osijek provides important insights into diet and subsistence in the Roman province of Pannonia. Here, the dominance of free-threshing wheat, spelt and rye with only a relatively small amount of other cereals, chaff and weeds corresponds well with this pattern seen elsewhere in Europe. The relatively clean grain deposit suggests that this sample represents processed grain ready for final food preparation and consumption at the villa. The morphological variation and overlap seen between the carbonised spelt and free-threshing wheat grains, as well as the identification of ‘stunted’ cereal grains, is also discussed

Surgical planning assistance in keyhole and percutaneous surgery: A systematic review

Surgical planning of percutaneous interventions has a crucial role to guarantee the success of minimally invasive surgeries. In the last decades, many methods have been proposed to reduce clinician work load related to the planning phase and to augment the information used in the definition of the optimal trajectory. In this survey, we include 113 articles related to computer assisted planning (CAP) methods and validations obtained from a systematic search on three databases. First, a general formulation of the problem is presented, independently from the surgical field involved, and the key steps involved in the development of a CAP solution are detailed. Secondly, we categorized the articles based on the main surgical applications, which have been object of study and we categorize them based on the type of assistance provided to the end-user