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IEEE Journal of Biomedical and Health Informatics
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4.22
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1446
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Published on Jan 1, 2018in IEEE Journal of Biomedical and Health Informatics4.22
Xiaoming Liu10
Estimated H-index: 10
(WUST: Wuhan University of Science and Technology),
Xiaoming Liu1
Estimated H-index: 1
+ 4 AuthorsKai Zhang2
Estimated H-index: 2
Optical coherence tomography (OCT) is a high-resolution and noninvasive imaging modality that has become one of the most prevalent techniques for ophthalmic diagnosis. Retinal layer segmentation is very crucial for doctors to diagnose and study retinal diseases. However, manual segmentation is often a time-consuming and subjective process. In this work, we propose a new method for automatically segmenting retinal OCT images, which integrates deep features and hand-designed features to train a st...
Published on Jan 1, 2018in IEEE Journal of Biomedical and Health Informatics4.22
Xiaoxi Pan , Mouloud Adel7
Estimated H-index: 7
+ 2 AuthorsEric Guedj27
Estimated H-index: 27
Using a single imaging modality to diagnose Alzheimer's disease (AD) or mild cognitive impairment (MCI) is a challenging task. FluoroDeoxyGlucose Positron Emission Tomography (FDG-PET) is an important and effective modality used for that purpose. In this paper, we develop a novel method by using single modality (FDG-PET) but multilevel feature, which considers both region properties and connectivities between regions to classify AD or MCI from normal control. First, three levels of features are ...
Published on Jan 1, 2018in IEEE Journal of Biomedical and Health Informatics4.22
Ruhul Amin11
Estimated H-index: 11
(International Institute of Information Technology),
Ruhul Amin3
Estimated H-index: 3
(International Institute of Information Technology)
+ 2 AuthorsNachiket Tapas2
Estimated H-index: 2
(UNIME: University of Messina)
Electronic health systems, such as telecare medical information system (TMIS), allow patients to exchange their health information with a medical center/doctor for diagnosis in real time, and across borders. Given the sensitive nature of health information/medical data, ensuring the security of such systems is crucial. In this paper, we revisit Das et al .'s authentication protocol, which is designed to ensure patient anonymity and untraceability. Then, we demonstrate that the security claims ar...
Published on Jan 1, 2018in IEEE Journal of Biomedical and Health Informatics4.22
Zengqiang Yan3
Estimated H-index: 3
(HKUST: Hong Kong University of Science and Technology),
Xin Yang9
Estimated H-index: 9
(HUST: Huazhong University of Science and Technology)
+ 0 AuthorsTim Cheng4
Estimated H-index: 4
(HKUST: Hong Kong University of Science and Technology)
Automatic retinal vessel segmentation is a fundamental step in the diagnosis of eye-related diseases, in which both thick vessels and thin vessels are important features for symptom detection. All existing deep learning models attempt to segment both types of vessels simultaneously by using a unified pixel-wise loss that treats all vessel pixels with equal importance. Due to the highly imbalanced ratio between thick vessels and thin vessels (namely the majority of vessel pixels belong to thick v...
Published on Jan 1, 2018in IEEE Journal of Biomedical and Health Informatics4.22
Didem Gokcay9
Estimated H-index: 9
,
Aykut Eken1
Estimated H-index: 1
,
Serdar Baltaci3
Estimated H-index: 3
Among several features used for clinical binary classification, behavioral performance, questionnaire scores, test results, and physical exam reports can be counted. Attempts to include neuroimaging findings to support clinical diagnosis are scarce due to difficulties in collecting such data, as well as problems in integration of neuroimaging findings with other features. The binary classification method proposed here aims to merge small samples from multiple sites so that a large cohort, which ...
Published on Jan 1, 2018in IEEE Journal of Biomedical and Health Informatics4.22
Miroslav Zivanovic3
Estimated H-index: 3
,
Nora Millor7
Estimated H-index: 7
,
Marisol Gómez11
Estimated H-index: 11
Objective : We present a novel approach to drift-free position estimation from noisy acceleration signals, which often arise from quasi-periodic small-amplitude body movements. In contrast to the existing methods, this data-driven strategy is designed to properly describe time-variant harmonic structures in single-channel acceleration signals for low signal-to-noise ratios. Methods : It comprises three processing steps: 1) short-time modeling of acceleration dynamics (instantaneous harmonic ampl...
Published on Jan 1, 2018in IEEE Journal of Biomedical and Health Informatics4.22
Aiying Zhang (Tulane University), Jian Fang5
Estimated H-index: 5
(Tulane University)
+ 2 AuthorsYu-Ping Wang20
Estimated H-index: 20
(Tulane University)
Schizophrenia (SZ) is a chronic and severe mental disorder that affects how a person thinks, feels, and behaves. It has been proposed that this disorder is related to disrupted brain connectivity, which has been verified by many studies. With the development of functional magnetic resonance imaging (fMRI), further exploration of brain connectivity was made possible. Region-based networks are commonly used for mapping brain connectivity. However, they fail to illustrate the connectivity within re...
Published on Jan 1, 2019in IEEE Journal of Biomedical and Health Informatics4.22
Darko Stern10
Estimated H-index: 10
,
Christian Payer5
Estimated H-index: 5
+ 1 AuthorsMartin Urschler15
Estimated H-index: 15
Age estimation from radiologic data is an important topic both in clinical medicine as well as in forensic applications, where it is used to assess unknown chronological age or to discriminate minors from adults. In this paper, we propose an automatic multi-factorial age estimation method based on MRI data of hand, clavicle, and teeth to extend the maximal age range from up to 19 years, as commonly used for age assessment based on hand bones, to up to 25 years, when combined with clavicle bones ...
Published on Jan 1, 2018in IEEE Journal of Biomedical and Health Informatics4.22
Nisha Ramesh3
Estimated H-index: 3
(UofU: University of Utah),
Tolga Tasdizen26
Estimated H-index: 26
(Scientific Computing and Imaging Institute)
Even though convolutional neural networks (CNN) have been used for cell segmentation, they require pixel-level ground truth annotations. This paper proposes a multitask learning algorithm for cell detection and segmentation using CNNs. We use dot annotations placed inside each cell indicating approximate cell centroids to create training datasets for the detection and segmentation tasks. The segmentation task is used to map the input image to foreground versus background regions, whereas the det...
Published on Jan 1, 2018in IEEE Journal of Biomedical and Health Informatics4.22
KyeongTaek Oh , Cheung Soo Shin9
Estimated H-index: 9
(Yonsei University)
+ 1 AuthorsSun Kook Yoo
In this paper, a method is proposed to measure human respiratory volume using a depth camera. The level-set segmentation method, combined with spatial and temporal information, was used to measure respiratory volume accurately. The shape of the human chest wall was used as spatial information. As temporal information, the segmentation result from the previous frame in the time-aligned depth image was used. The results of the proposed method were verified using a ventilator. The proposed method w...
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