A Deep Learning Framework for Unsupervised Affine and Deformable Image Registration

Image registration, the process of aligning two or more images, is the core technique of many (semi-)automatic medical image analysis tasks. Recent studies have shown that deep learning methods, notably convolutional neural networks (ConvNets), can be used for image registration. Thus far training of ConvNets for registration was supervised using predefined example registrations. However, obtaining example registrations is not trivial. To circumvent the need for predefined examples, and thereby to increase convenience of training ConvNets for image registration, we propose the Deep Learning Image Registration (DLIR) framework for \textit{unsupervised} affine and deformable image registration. In the DLIR framework ConvNets are trained for image registration by exploiting image similarity analogous to conventional intensity-based image registration. After a ConvNet has been trained with the DLIR framework, it can be used to register pairs of unseen images in one shot. We propose flexible ConvNets designs for affine image registration and for deformable image registration. By stacking multiple of these ConvNets into a larger architecture, we are able to perform coarse-to-fine image registration. We show for registration of cardiac cine MRI and registration of chest CT that performance of the DLIR framework is comparable to conventional image registration while being several orders of magnitude faster.Comment: Accepted: Medical Image Analysis - Elsevie

Strongly nonexponential time-resolved fluorescence of quantum-dot ensembles in three-dimensional photonic crystals

We observe experimentally that ensembles of quantum dots in three-dimensional (3D) photonic crystals reveal strongly nonexponential time-resolved emission. These complex emission decay curves are analyzed with a continuous distribution of decay rates. The log-normal distribution describes the decays well for all studied lattice parameters. The distribution width is identified with variations of the radiative emission rates of quantum dots with various positions and dipole orientations in the unit cell. We find a striking sixfold change of the width of the distribution by varying the lattice parameter. This interpretation qualitatively agrees with the calculations of the 3D projected local density of states. We therefore conclude that fluorescence decay of ensembles of quantum dots is highly nonexponential to an extent that is controlled by photonic crystals

Penerapan Teknologi General Packet Radio Service Pada Sistem Monitoring Sepeda Motor

General Packet Radio Service (GPRS) merupakan sistem transmisi berbasis paket untuk Global System for Mobile (GSM). Pengembangan sistem keamanan menggunakan GPRS merupakan salah satu bidang yang terus mengalami pembaharuan terutama di negara Indonesia dimana keamanan masih menjadi salah satu fokus dalam perbaikan. Tingkat keamanan kendaraan terutama sepeda motor di Indonesia masih sangat kurang terjamin, hal ini menjadi latar belakang tugas akhir ini dirancang. Alat ini dirancang untuk dapat memberikan informasi tentang keberadaan sepeda motor baik dalam informasi kehilangan maupun informasi posisi kendaraan. Data mengenai informasi kehilangan akan dikirimkan langsung ke Handphone pengguna dengan transmisi GSM dan data mengenai informasi posisi berupa data lintang dan bujur akan dikirimkan menuju database yang dibuat dengan menggunakan MySQl melalui GPRS serta dapat diakses menggunakan website dengan halaman utama menggunakan HyperText Markup Language (HTML) dan koneksi dengan Google Maps API. Peta dasar yang dinamis membuat akurasi yang lebih baik antara data pelacakan dengan penandaan posisi pada peta. Data mengenai posisi akan didapat melalui Global Positioning System (GPS) yang kemudian data tersebut akan diolah menjadi data yang siap dikonversikan pada peta dan dalam bentuk sebuah marker

Study protocol ROTATE-trial:anterior cruciate ligament rupture, the influence of a treatment algorithm and shared decision making on clinical outcome- a cluster randomized controlled trial

BACKGROUND: Anterior cruciate ligament (ACL) rupture is a very common knee injury in the sport active population. There is much debate on which treatment (operative or non-operative) is best for the individual patient. In order to give a more personalized recommendation we aim to evaluate the effectiveness and cost-effectiveness of a treatment algorithm for patients with a complete primary ACL rupture. METHODS: The ROTATE-trial is a multicenter, open-labeled cluster randomized controlled trial with superiority design. Randomization will take place on hospital level (n = 10). Patients must meet all the following criteria: aged 18 year or older, with a complete primary ACL rupture (confirmed by MRI and physical examination) and maximum of 6 weeks of non-operative treatment. Exclusion criteria consists of multi ligament trauma indicated for surgical intervention, presence of another disorder that affects the activity level of the lower limb, pregnancy, and insufficient command of the Dutch language. The intervention to be investigated will be an adjusted treatment decision strategy, including an advice from our treatment algorithm. Patient reported outcomes will be conducted at baseline, 3, 6, 12 and 24 months. Physical examination of the knee at baseline, 12 and 24 months. Primary outcome will be function of the knee measured by the International Knee Documentation Committee (IKDC) questionnaire. Secondary outcomes are, among others, the Tegner activity score, the Knee injury and Osteoarthritis Outcome Score (KOOS) and the 9-item Shared Decision Making Questionnaire (SDM-Q-9). Healthcare use, productivity and satisfaction with ((non-)operative) care are also measured by means of questionnaires. In total 230 patients will be included, resulting in 23 patients per hospital. DISCUSSION: The ROTATE study aims to evaluate the effectiveness and cost-effectiveness of a treatment algorithm for patients with a complete primary ACL rupture compared to current used treatment strategy. Using a treatment algorithm might give the much-wanted personalized treatment recommendation. TRIAL REGISTRATION: This study is approved by the Medical Research Ethics Committee of Erasmus Medical Center in Rotterdam and prospectively registered at the Dutch Trial Registry on May 13th, 2020. Registration number: NL8637.</p

Automated extraction of potential migraine biomarkers using a semantic graph

Problem Biomedical literature and databases contain important clues for the identification of potential disease biomarkers. However, searching these enormous knowledge reservoirs and integrating findings across heterogeneous sources is costly and difficult. Here we demonstrate how semantically integrated knowledge, extracted from biomedical literature and structured databases, can be used to automatically identify potential migraine biomarkers. Method We used a knowledge graph containing more than 3.5 million biomedical concepts and 68.4 million relationships. Biochemical compound concepts were filtered and ranked by their potential as biomarkers based on their connections to a subgraph of migraine-related concepts. The ranked results were evaluated against the results of a systematic literature review that was performed manually by migraine researchers. Weight points were assigned to these reference compounds to indicate their relative importance. Results Ranked results automatically generated by the knowledge graph were highly consistent with results from the manual literature review. Out of 222 reference compounds, 163 (73%) ranked in the top 2000, with 547 out of the 644 (85%) weight points assigned to the reference compounds. For reference compounds that were not in the top of the list, an extensive error analysis has been performed. When evaluating the overall performance, we obtained a ROC-AUC of 0.974. Discussion Semantic knowledge graphs composed of information integrated from multiple and varying sources can assist researchers in identifying potential disease biomarkers

Subanalytic sets and feedback control

AbstractThe theory of subanalytic sets is used to prove: If a real analytic control system is completely controllable, then for every point p in the state space there exists a piecewise analytic feedback control that steers every state into p

Externally validated treatment algorithm acceptably predicts nonoperative treatment success in patients with anterior cruciate ligament rupture

Purpose: This study aims to develop and externally validate a treatment algorithm to predict nonoperative treatment success or failure in patients with anterior cruciate ligament (ACL) rupture. Methods: Data were used from two completed studies of adult patients with ACL ruptures: the Conservative versus Operative Methods for Patients with ACL Rupture Evaluation study (development cohort) and the KNee osteoArthritis anterior cruciate Ligament Lesion study (validation cohort). The primary outcome variable is nonoperative treatment success or failure. Potential predictor variables were collected, entered into the univariable logistic regression model and then incorporated into the multivariable logistic regression model for constructing the treatment algorithm. Finally, predictive performance and goodness-of-fit were assessed and externally validated by discrimination and calibration measures. Results: In the univariable logistic regression model, a stable knee measured with the pivot shift test and a posttrauma International Knee Documentation Committee (IKDC) score &lt;50 were predictive of needing an ACL reconstruction. Age &gt;30 years and a body mass index &gt; 30 kg/m2 were predictive for not needing an ACL reconstruction. Age, pretrauma Tegner score, the outcome of the pivot shift test and the posttrauma IKDC score are entered into the treatment algorithm. The predictability of needing an ACL reconstruction after nonoperative treatment (discrimination) is acceptable in both the development and the validation cohort: area under the curve = resp. 0.69 (95% confidence interval [CI]: 0.58–0.81) and 0.68 (95% CI: 0.58–0.78). Conclusion: This study shows that the treatment algorithm can acceptably predict whether an ACL injury patient will have a(n) (un)successful nonoperative treatment (discrimination). Calibration of the treatment algorithm suggests a systematical underestimation of the need for ACL reconstruction. Given the limitations regarding the sample size of this study, larger data sets must be constructed to improve the treatment algorithm further. Level of Evidence: Level II.</p

Specific protein homeostatic functions of small heat-shock proteins increase lifespan

During aging, oxidized, misfolded, and aggregated proteins accumulate in cells, while the capacity to deal with protein damage declines severely. To cope with the toxicity of damaged proteins, cells rely on protein quality control networks, in particular proteins belonging to the family of heat-shock proteins (HSPs). As safeguards of the cellular proteome, HSPs assist in protein folding and prevent accumulation of damaged, misfolded proteins. Here, we compared the capacity of all Drosophila melanogaster small HSP family members for their ability to assist in refolding stress-denatured substrates and/or to prevent aggregation of disease-associated misfolded proteins. We identified CG14207 as a novel and potent small HSP member that exclusively assisted in HSP70-dependent refolding of stress-denatured proteins. Furthermore, we report that HSP67BC, which has no role in protein refolding, was the most effective small HSP preventing toxic protein aggregation in an HSP70-independent manner. Importantly, overexpression of both CG14207 and HSP67BC in Drosophila leads to a mild increase in lifespan, demonstrating that increased levels of functionally diverse small HSPs can promote longevity in vivo

β2→ 1-fructans modulate the immune system in vivo by direct interaction with the mucosa in a microbiota-independent fashion

It has been shown in vitro that only specific dietary fibers contribute to immunity, but studies in vivo are not conclusive. Here, we investigated degree of polymerization (DP) dependent effects of beta2-->1-fructans on immunity via microbiota-dependent and -independent effects. To this end, conventional or germ-free mice received short- or long-chain beta2-->1-fructan for 5 days. Immune cell populations in the spleen, mesenteric lymph nodes (MLNs), and Peyer's patches (PPs) were analyzed with flow cytometry, genome-wide gene expression in the ileum was measured with microarray, and gut microbiota composition was analyzed with 16S rRNA sequencing of fecal samples. We found that beta2-->1-fructans modulated immunity by both microbiota and microbiota-independent effects. Moreover, effects were dependent on the chain-length of the beta2-->1-fructans type polymer. Both short- and long-chain beta2-->1-fructans enhanced T-helper 1 cells in PPs, whereas only short-chain beta2-->1-fructans increased regulatory T cells and CD11b-CD103- dendritic cells (DCs) in the MLN. A common feature after short- and long-chain beta2-->1-fructan treatment was enhanced 2-alpha-l-fucosyltransferase 2 expression and other IL-22-dependent genes in the ileum of conventional mice. These effects were not associated with shifts in gut microbiota composition, or altered production of short-chain fatty acids. Both short- and long-chain beta2-->1-fructans also induced immune effects in germ-free animals, demonstrating direct effect independent from the gut microbiota. Also, these effects were dependent on the chain-length of the beta2-->1-fructans. Short-chain beta2-->1-fructan induced lower CD80 expression by CD11b-CD103- DCs in PPs, whereas long-chain beta2-->1-fructan specifically modulated B cell responses in germ-free mice. In conclusion, support of immunity is determined by the chemical structure of beta2-->1-fructans and is partially microbiota independent