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Vision training

Guillaume Pagès, Benoit Charmettant, Sergei Grudinin
MOTIVATION: Protein model quality assessment (QA) is a crucial and yet open problem in structural bioinformatics. The current best methods for single-model QA typically combine results from different approaches, each based on different input features constructed by experts in the field. Then, the prediction model is trained using a machine-learning algorithm. Recently, with the development of convolutional neural networks (CNN), the training paradigm has changed. In computer vision, the expert-developed features have been significantly overpassed by automatically trained convolutional filters...
February 19, 2019: Bioinformatics
Damien Joubert, Mathieu Hébert, Hubert Konik, Christophe Lavergne
Event-based cameras bring new perspectives for perception systems by making them faster, smarter, and less energy-consuming. While they are spreading into many application domains, new algorithms are designed to process the data they provide, and new databases are needed to validate and train them. Simulations are an efficient way to increase databases, as they give direct access to ground truth for applications such as target detection or depth estimation, provided the simulation models used are as close as possible to the physical reality...
February 20, 2019: Applied Optics
Amr Elkholy, Mohamed Hussein, Walid Gomaa, Dima Damen, Emmanuel Saba
Elderly people can be provided with safer and more independent living by the early detection of abnormalities in their performing of actions and the frequent assessment of the quality of their motion. Low-cost depth sensing is one of the emerging technologies that can be used for unobtrusive and inexpensive motion abnormality detection and quality assessment. In this study, we develop and evaluate vision-based methods to detect and assess neuromusculoskeletal disorders manifested in common daily activities using 3D skeletal data provided by the SDK of a depth camera (e...
March 11, 2019: IEEE Journal of Biomedical and Health Informatics
Sorour Mohajerani, Parvaneh Saeedi
Automatic identification of shadow regions in an image is a basic and yet very important task in many computer vision applications such as object detection, target tracking, and visual data analysis. Although shadow detection is a well-studied topic, current methods for identification of shadow are not as accurate as required. In this work, we propose a deep-learning method for shadow detection at a pixel-level that is suitable for single RGB images. The proposed CNN-based method benefits from a novel architecture through which global and local shadow attributes are identified using a new and efficient mapping scheme in the skip connection...
March 11, 2019: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Qidan Zhu, Yu Han, Peng Liu, Yao Xiao, Peng Lu, Chengtao Cai
This paper proposes a novel motion planning method for an autonomous ground mobile robot to address dynamic surroundings, nonlinear program, and robust optimization problems. A planner based on the recurrent fuzzy neural network (RFNN) is designed to program trajectory and motion of mobile robots to reach target. And, obstacle avoidance is achieved. In RFNN, inference capability of fuzzy logic and learning capability of neural network are combined to improve nonlinear programming performance. A recurrent frame with self-feedback loops in RFNN enhances stability and robustness of the structure...
2019: Computational Intelligence and Neuroscience
Edsel B Ing, Neil R Miller, Angeline Nguyen, Wanhua Su, Lulu L C D Bursztyn, Meredith Poole, Vinay Kansal, Andrew Toren, Dana Albreki, Jack G Mouhanna, Alla Muladzanov, Mikaël Bernier, Mark Gans, Dongho Lee, Colten Wendel, Claire Sheldon, Marc Shields, Lorne Bellan, Matthew Lee-Wing, Yasaman Mohadjer, Navdeep Nijhawan, Felix Tyndel, Arun N E Sundaram, Martin W Ten Hove, John J Chen, Amadeo R Rodriguez, Angela Hu, Nader Khalidi, Royce Ing, Samuel W K Wong, Nurhan Torun
Purpose: To develop and validate neural network (NN) vs logistic regression (LR) diagnostic prediction models in patients with suspected giant cell arteritis (GCA). Design: Multicenter retrospective chart review. Methods: An audit of consecutive patients undergoing temporal artery biopsy (TABx) for suspected GCA was conducted at 14 international medical centers. The outcome variable was biopsy-proven GCA. The predictor variables were age, gender, headache, clinical temporal artery abnormality, jaw claudication, vision loss, diplopia, erythrocyte sedimentation rate, C-reactive protein, and platelet level...
2019: Clinical Ophthalmology
Tao Chen, Mark Dredze, Jonathan P Weiner, Leilani Hernandez, Joe Kimura, Hadi Kharrazi
BACKGROUND: Geriatric syndromes in older adults are associated with adverse outcomes. However, despite being reported in clinical notes these syndromes are often poorly captured by diagnostic codes in the structured fields of electronic health records (EHRs) or administrative records. OBJECTIVE: We aim to automatically determine if a patient has any geriatric syndromes by mining the free text of associated EHR clinical notes. We assessed which statistical natural language processing (NLP) techniques are most effective...
March 7, 2019: JMIR Medical Informatics
Linda S Petty, Julia E G Foster, Patty Rigby
BACKGROUND.: Co-occurring mobility issues and vision loss are prevalent in older adults. Vision loss can cause ambulation difficulties and falls. Community-dwelling older adults frequently require mobility-aids assessment by occupational therapists. However, therapists often lack access to medical documentation on vision or training in vision assessment to ensure that clients have adequate vision for safe mobility-aid use. PURPOSE.: This study aimed to identify screening and assessment approaches to identify functional vision loss to guide mobility-aid prescription...
March 12, 2019: Canadian Journal of Occupational Therapy. Revue Canadienne D'ergothérapie
Mina Boazak, Robert Cotes
IntroductionFacial expressivity in schizophrenia has been a topic of clinical interest for the past century. Besides the schizophrenia sufferers difficulty decoding the facial expressions of others, they often have difficulty encoding facial expressions. Traditionally, evaluations of facial expressions have been conducted by trained human observers using the facial action coding system. The process was slow and subject to intra and inter-observer variability. In the past decade the traditional facial action coding system developed by Ekman has been adapted for use in affective computing...
February 2019: CNS Spectrums
Mohammed Khaled Al-Hanawi, Sami A Khan, Hussein Mohammed Al-Borie
Background: Saudi Arabia is currently passing through a transformational phase. There is a huge demand on the Saudi healthcare system to provide better healthcare facilities to the rapidly increasing Saudi population, as well as the growing elderly population. Lack of trained healthcare professionals and heavy reliance on foreign workers are significant aspects for policymakers to consider and deal with. It is also important to re-examine the healthcare Human Resource Development (HRD) initiatives so as to provide a huge reserve of healthcare professionals with appropriate learning and competence...
2019: Public Health Reviews
Andrew M Williams, Benjamin Botsford, Peter Mortensen, Daniel Park, Evan L Waxman
Objective: The objective of the study was to characterize the population served by the student-led Guerrilla Eye Service (GES), a mobile outreach program that delivers comprehensive ophthalmic care to underserved communities in the greater Pittsburgh area. Patients and methods: Patients attending GES missions at a single urban free clinic from 2012 through 2017 were included in this retrospective case series. All patients underwent a comprehensive eye examination at no cost, with referral to a university eye clinic if necessary...
2019: Clinical Ophthalmology
Donghuan Lu, Morgan Heisler, Sieun Lee, Gavin Weiguang Ding, Eduardo Navajas, Marinko V Sarunic, Mirza Faisal Beg
As a non-invasive imaging modality, optical coherence tomography (OCT) can provide micrometer-resolution 3D images of retinal structures. These images can help reveal disease-related alterations below the surface of the retina, such as the presence of edema, or accumulation of fluid which can distort vision, and are an indication of disruptions in the vasculature of the retina. In this paper, a new framework is proposed for multiclass fluid segmentation and detection in the retinal OCT images. Based on the intensity of OCT images and retinal layer segmentations provided by a graph-cut algorithm, a fully convolutional neural network was trained to recognize and label the fluid pixels...
February 22, 2019: Medical Image Analysis
M Noorjahan, A Punitha
PURPOSE: In the context of assistive technology, mobility takes the meaning of "moving safely, gracefully, and comfortably".The aim of this article is to provide a system which will be a convenient means of navigation for the Visually Impaired people, in the public transport system. METHOD: A blind regular commuter who travels by public transport facility finds difficulty in identifying the vehicle that is nearing the stop. Hence, a real-time system that dynamically identifies the nearing vehicle and informs the commuters is necessary...
March 11, 2019: Disability and Rehabilitation. Assistive Technology
Titus J Brinker, Achim Hekler, Alexander H Enk, Joachim Klode, Axel Hauschild, Carola Berking, Bastian Schilling, Sebastian Haferkamp, Dirk Schadendorf, Stefan Fröhling, Jochen S Utikal, Christof von Kalle
BACKGROUND: Recent studies have demonstrated the use of convolutional neural networks (CNNs) to classify images of melanoma with accuracies comparable to those achieved by board-certified dermatologists. However, the performance of a CNN exclusively trained with dermoscopic images in a clinical image classification task in direct competition with a large number of dermatologists has not been measured to date. This study compares the performance of a convolutional neuronal network trained with dermoscopic images exclusively for identifying melanoma in clinical photographs with the manual grading of the same images by dermatologists...
March 7, 2019: European Journal of Cancer
Campagner Dario, Evans H Mathew, Chlebikova Katarina, Colins-Rodriguez Andrea, Loft S E Michaela, Fox Sarah, Pettifer David, Humphries D Mark, Svoboda Karel, Petersen S Rasmus
Perceptual decision making is an active process where animals move their sense organs to extract task-relevant information. To investigate how the brain translates sensory input into decisions during active sensation, we developed a mouse active touch task where the mechanosensory input can be precisely measured and that challenges animals to use multiple mechanosensory cues. Male mice were trained to localise a pole using a single whisker and to report their decision by selecting one of three choices. Using high-speed imaging and machine vision we estimated whisker-object mechanical forces at millisecond resolution...
March 8, 2019: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
Michael D Richards, Herbert C Goltz, Agnes M F Wong
Purpose: Evidence from animals and blind humans suggests that early visual experience influences the developmental calibration of auditory localization. Hypothesizing that unilateral amblyopia may involve cross-modal deficits in spatial hearing, we measured the precision and accuracy of sound localization in humans with amblyopia. Methods: All participants passed a standard hearing test. Experiment 1 measured sound localization precision for click stimuli in 10 adults with amblyopia and 10 controls using a minimum audible angle (MAA) task...
March 1, 2019: Investigative Ophthalmology & Visual Science
Olle Ten Cate, Carol Carraccio
The existing structure of physician education has developed in siloed stages, with consecutive degrees and certifications and progressively longer training programs. As further fragmentation of health care and training systems will not improve the quality of care and education, the authors argue that a new vision of education, training, and practice as a continuum is needed.They advocate for a model of competency-based medical education that merges with competency-based medical practice. In this system, education and training will result in individual, dynamic portfolios of valid entrustable professional activities (EPAs) for which physicians are certified...
March 5, 2019: Academic Medicine: Journal of the Association of American Medical Colleges
Gloria E Zambrano-Plata, Luz M Bautista-Rodríguez, Valeria S López
OBJECTIVE : To describe and explain imaginaries about sexuality that university students have at the beginning of their professional training. METHODS : Study with a qualitative approach, for which grounded theory was used as methodology and method. 11 students enrolled in the first semester of different undergraduate programs were included. The information was collected through 25 in-depth interviews, with an average of two interviews per reporter. RESULTS : Six categories emerged from the data: socialization of sexuality in the family; socialization of sexuality in the school; socialization of sexuality in the media; socialization of sexuality with peers; traditional imaginary of sexuality; and liberal imaginary of sexuality...
July 2018: Revista de Salud Pública
Abhijith Punnappurath, Michael S Brown
Deep learning-based image compressors are actively being explored in an effort to supersede conventional image compression algorithms, such as JPEG. Conventional and deep learning-based compression algorithms focus on minimizing image fidelity errors in the nonlinear standard RGB (sRGB) color space. However, for many computer vision tasks, the sensor's linear raw-RGB image is desirable. Recent work has shown that the original raw-RGB image can be reconstructed using only small amounts of metadata embedded inside the JPEG image [1]...
March 4, 2019: IEEE Transactions on Pattern Analysis and Machine Intelligence
Kosuke Nomura, Daisuke Kikuchi, Mitsuru Kaise, Toshiro Iizuka, Yorinari Ochiai, Yugo Suzuki, Yumiko Fukuma, Masami Tanaka, Yosuke Okamoto, Satoshi Yamashita, Akira Matsui, Toshifumi Mitani, Shu Hoteya
BACKGROUND AND OBJECTIVES: Conventional endoscopy provides two-dimensional (2D) information without depth information. This study compared three-dimensional (3D) endoscopy and 2D endoscopy using an endoscopic submucosal dissection (ESD) training model to evaluate the utility of 3D endoscopy. METHODS: Porcine stomach specimens (7 × 7 cm) were prepared from commercially available resected porcine stomachs and a 10-mm hypothetical lesion was marked at the center of each specimen...
March 6, 2019: Surgical Endoscopy
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