Interactive Medical Image Segmentation using Deep Learning with Image-specific Fine-tuning

Convolutional neural networks (CNNs) have achieved state-of-the-art performance for automatic medical image segmentation. However, they have not demonstrated sufficiently accurate and robust results for clinical use. In addition, they are limited by the lack of image-specific adaptation and the lack of generalizability to previously unseen object classes. To address these problems, we propose a novel deep learning-based framework for interactive segmentation by incorporating CNNs into a bounding box and scribble-based segmentation pipeline. We propose image-specific fine-tuning to make a CNN model adaptive to a specific test image, which can be either unsupervised (without additional user interactions) or supervised (with additional scribbles). We also propose a weighted loss function considering network and interaction-based uncertainty for the fine-tuning. We applied this framework to two applications: 2D segmentation of multiple organs from fetal MR slices, where only two types of these organs were annotated for training; and 3D segmentation of brain tumor core (excluding edema) and whole brain tumor (including edema) from different MR sequences, where only tumor cores in one MR sequence were annotated for training. Experimental results show that 1) our model is more robust to segment previously unseen objects than state-of-the-art CNNs; 2) image-specific fine-tuning with the proposed weighted loss function significantly improves segmentation accuracy; and 3) our method leads to accurate results with fewer user interactions and less user time than traditional interactive segmentation methods.Comment: 11 pages, 11 figure

Hippocampus Leads Ventral Striatum in Replay of Place-Reward Information

While the brain is asleep, the hippocampus plays first fiddle in the orchestra of memory; spatial information is reactivated in the hippocampus shortly in advance of emotional memory traces in the vental striatum

Epilepsy is related to theta band brain connectivity and network topology in brain tumor patients

<p>Abstract</p> <p>Background</p> <p>Both epilepsy patients and brain tumor patients show altered functional connectivity and less optimal brain network topology when compared to healthy controls, particularly in the theta band. Furthermore, the duration and characteristics of epilepsy may also influence functional interactions in brain networks. However, the specific features of connectivity and networks in tumor-related epilepsy have not been investigated yet. We hypothesize that epilepsy characteristics are related to (theta band) connectivity and network architecture in operated glioma patients suffering from epileptic seizures. Included patients participated in a clinical study investigating the effect of levetiracetam monotherapy on seizure frequency in glioma patients, and were assessed at two time points: directly after neurosurgery (t1), and six months later (t2). At these time points, magnetoencephalography (MEG) was recorded and information regarding clinical status and epilepsy history was collected. Functional connectivity was calculated in six frequency bands, as were a number of network measures such as normalized clustering coefficient and path length.</p> <p>Results</p> <p>At the two time points, MEG registrations were performed in respectively 17 and 12 patients. No changes in connectivity or network topology occurred over time. Increased theta band connectivity at t1 and t2 was related to a higher total number of seizures. Furthermore, higher number of seizures was related to a less optimal, more random brain network topology. Other factors were not significantly related to functional connectivity or network topology.</p> <p>Conclusions</p> <p>These results indicate that (pathologically) increased theta band connectivity is related to a higher number of epileptic seizures in brain tumor patients, suggesting that theta band connectivity changes are a hallmark of tumor-related epilepsy. Furthermore, a more random brain network topology is related to greater vulnerability to seizures. Thus, functional connectivity and brain network architecture may prove to be important parameters of tumor-related epilepsy.</p

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong

Beauty in the Middle Ages: A Forgotten Transcendental?

Page range: 68-9

The Beginnings of Transcendental Philosophy

The paper presents the sources and the development of the medieval doctrine of transcendentals. In Aertsen's opinion transcendental philosophy of the Middle Ages differs considerably from the ontological doctrine of the Ancients as well as from the modern theory referring to the sphere of cognition. The beginnings of the medieval doctrine of the transcendentals were inspired mostly by considerations concerning primary conceptions of human mind included in Avicenna's "Metaphysica". Furthermore, they were connected with the Aristotelian idea of science, the Boethian axiomatic method of "common conceptions of the soul", and theologians' interest in the horizon of human intellectual knowledge. Beside the Aristotelian-Avicennian reduction to the most universal predicate Albert the Great acknowledge another reduction (originating from the Christian-Neoplatonic tradition): reduction to the first cause. In his opinion, these two resolutions are complementary to each other. In the philosophy of Thomas Aquinas, transcendentals are most fundamental insofar as they are the foundations of theoretical and practical science. The principle of contradiction – considered as the beginning of theoretical science – rests on the understanding of "being", and the first precept of natural law is founded on "the good". The development of the doctrine of the transcendentals in 13th century aloows to call the period "the second beginning of metaphysics" – since it changes the understanding of the proper subject of First Philosophy. In Albert the Great, for example, matephysics ceases to be the science of the divine, and becomes the science concerning what is first and the most fundamental – "being-as-being". In St. Bonaventure's philosophy, the doctrine of the transcendentals undergoes a theologizing transformation: that, which is first in the cognitive order is, at the same time, first ontologically. For Bonaventure, the latter "first" is God.Jest to tłumaczenie tekstu "What is First and Most Fundamental? – The Beginnings of Transcendental Philosophy", który ukazał się w "Miscellanea Mediaevalia" 1998, vol. 26, s. 177-192. Przełożył Robert Podkoński, przejrzał i poprawił Marek Gensler