Adaptive intelligence aims at empowering machine learning techniques with the additional use of domain knowledge. In this work, we present application adaptive to accelerate MR acquisition. Starting from undersampled k-space data, an iterative learning-based reconstruction scheme inspired by compressed sensing theory is used reconstruct images. We developed a novel deep neural network refine and correct prior assumptions given training data. The was trained tested on knee MRI dataset 2019...

Purpose To develop and validate a robust accurate registration pipeline for automatic contour propagation online adaptive Intensity‐Modulated Proton Therapy (IMPT) of prostate cancer using elastix software deep learning. Methods A three‐dimensional (3D) Convolutional Neural Network was trained bladder segmentation the computed tomography (CT) scans. The alongside scan is jointly optimized to add explicit knowledge about underlying anatomy algorithm. We included three datasets from different...

The attachment a mother feels for her fetus intensifies duty to care it, leading heightened desire engage in behaviors that promote health. This research explored the association between maternal-fetal (MFA) and adherence health-related among pregnant women. cross-sectional study focused on 220 women Jahrom City, was conducted using multi-stage random sampling strategy. data were collected Maternal-Fetal Attachment Scale paired with questionnaire addressed health relevant pregnancy. analyzed...

We propose a supervised nonrigid image registration method, trained using artificial displacement vector fields (DVF), for which we and compare three network architectures. The DVFs allow training in fully voxel-wise dense manner, but without the cost usually associated with creation of densely labeled data. scheme to artificially generate DVFs, chest CT augment these simulated respiratory motion. proposed architectures are embedded multi-stage approach, increase capture range networks order...

Parallel RF transmission (PTx) is one of the key technologies enabling high quality imaging at ultra-high fields (≥7T). Compliance with regulatory limits on local specific absorption rate (SAR) typically involves over-conservative safety margins to account for intersubject variability, which negatively affect utilization field MR. In this work, we present a method generate subject-specific body model from single T1-weighted dataset personalized SAR prediction in PTx neuroimaging...

In this paper we propose a supervised method to predict registration misalignment using convolutional neural networks (CNNs). This task is casted classification problem with multiple classes of misalignment: "correct" 0-3 mm, "poor" 3-6 mm and "wrong" over 6 mm. Rather than direct prediction, hierarchical approach, where the prediction gradually refined from coarse fine. Our solution based on Long Short-Term Memory (LSTM), predictions three resolutions image pair, leveraging intrinsic...

To report the method and results of 18-point Abobotulinum toxin A (ABO-BTA, Dysport) upper face rejuvenation on 845 subjects.In a retrospective chart review, all subjects (the first cycle injection) with ABO-BTA from 2003 to 2009 were included. Excluded facial spastic disorders, injection after lifting, aberrant regeneration nerves. Upper included 18 points at forehead creases (4), frown lines (5), bunny line (1), crow's feet (4 both sides), lower eyelid crease sides). They revisited in 10...

Medical image registration and segmentation are two of the most frequent tasks in medical analysis. As these complementary correlated, it would be beneficial to apply them simultaneously a joint manner. In this paper, we formulate as problem via Multi-Task Learning (MTL) setting, allowing leverage their strengths mitigate weaknesses through sharing information. We propose merge not only on loss level, but architectural level well. studied approach context adaptive image-guided radiotherapy...

Recently, there has been a considerable attention given to the motion detection problem due explosive growth of its applications in video analysis and surveillance systems. While previous approaches can produce good results, an accurate remains challenging task difficulties raised by illumination variations, occlusion, camouflage, burst physical motion, dynamic texture, environmental changes such as those on climate changes, sunlight during day, etc. In this paper, we propose novel per-pixel...

Objectives: We assessed the effect of selenium and zinc supplementation on CD4 cell count risk developing opportunistic infections.Methods: In a double blind clinical trial, 146 HIV(+) patients receiving combination antiretroviral therapy with CD4(+) >200/cubic millimeter were screened for comorbidities infections, randomized to receive daily (200 µg), (50 mg) or placebo 6 months, before 3-month follow-up period. counts measured in 3th, 6th 9th months. The serum month. incidence infection...

Adaptive intelligence aims at empowering machine learning techniques with the extensive use of domain knowledge. In this work, we present application adaptive to accelerate MR acquisition. Starting from undersampled k-space data, an iterative learning-based reconstruction scheme inspired by compressed sensing theory is used reconstruct images. We adopt deep neural networks refine and correct prior assumptions given training data. Our results show that approach performs better than...

This paper presents a lossless data hiding method using integer wavelet transform. The modification of small coefficients the high frequency subbands are used to embed data. We use histogram prepare enough space for hiding. Data embedding is done by processing these selected modified subband histograms. show that we can capacity applying multi-level decomposition and modification. Experimental results our outperforms prior arts in terms larger pay-load.

Background: Acquired immune deficiency syndrome (AIDS) is believed to be both among major epidemics and a critical global health issue. The administration of antiretroviral therapy recently proposed for all patients with CD4 + T cell count ≤ 350/μlit in different studies accessibility combination has been restricted due high costs drugs, particularly low middle income countries. In Iran, according WHO, drugs were distributed only 6% adults 4% - 14% children 2009. Moreover, new strains are...

Background and purpose: Available data indicate the quality of doctor-patient communication has a significant impact on patient satisfaction, medical outcomes, costs, likelihood physician experiencing malpractice claim. Assessment skills is very important issue. Since good assessment can show strengths weaknesses this process feedback improve behavior, study was designed to measure skill last year students (interns) in Jahrom school by an observational checklist. Methods: This cross...

This paper presents a lossless data hiding method using coefficients of integer wavelet domain. The modification selected small the high frequency subbands are used to embed data. We use histogram intelligently select proper for hiding. Data embedding is done by processing these coefficients. show that at low payload our has comparable PSNR than best known reversible techniques, while higher payloads it significant superiority on image quality.

Adaptive intelligence aims at empowering machine learning techniques with the additional use of domain knowledge. In this work, we present application adaptive to accelerate MR acquisition. Starting from undersampled k-space data, an iterative learning-based reconstruction scheme inspired by compressed sensing theory is used reconstruct images. We adopt deep neural networks refine and correct prior assumptions given training data. The network was trained tested on a knee MRI dataset 2019...

This paper introduces DONUT-hole, a sparse OCR-free visual document understanding (VDU) model that addresses the limitations of its predecessor model, dubbed DONUT. The DONUT leveraging transformer architecture, overcoming challenges separate optical character recognition (OCR) and semantic (VSU) components. However, deployment in production environments edge devices is hindered by high memory computational demands, particularly large-scale request services. To overcome these challenges, we...

This paper proposes a robust approach for face detection and gender classification in color images. Previous researches about recognition suppose an expensive computational time-consuming pre-processing step order to alignment which images are aligned so that facial landmarks like eyes, nose, lips, chin placed uniform locations image. In this paper, novel technique based on mathematical analysis is represented three stages eliminates step. First, new method with better result more robustness...

In this paper, we propose a method for cryptanalysis of the Shi reversible data hiding algorithm. We also to improve its security by using concepts in number theory. Our improvement part encrypts four keys before embedding it digital image and detection are used as side information recover original data. Theoretical analysis experimental results shows that finding from marked after applying our proposed algorithm is not feasible reasonable time.