Results 51 to 60 of about 1,138,724 (269)
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Oral mucositis is a common and debilitating side effect of childhood cancer and stem cell transplant treatments. It affects the quality of life of children and young people (CYP) and places a strain on services. Photobiomodulation is recommended for oral mucositis prevention in international guidance but is poorly implemented in UK ...
Claudia Heggie +4 more
wiley +1 more source
Image deblurring method driven by double layer convolution neural network denoising module
Nantong Daxue xuebao. Ziran kexue ban, 2022 To solve this problem for inflexible of noise levels for deep convolution neural network for image denoising, an image deblurring method driven by a double deep convolution neural network for image denoising is proposed.The learning capability of ...
WU Jingjing; MA Jingning; ZHU Yonggui
doaj +1 more source
Domain and Geometry Agnostic CNNs for Left Atrium Segmentation in 3D Ultrasound
, 2018 Segmentation of the left atrium and deriving its size can help to predict and detect various cardiovascular conditions. Automation of this process in 3D Ultrasound image data is desirable, since manual delineations are time-consuming, challenging and ...
A Rohner +8 more
core +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Objective To evaluate selumetinib exposure using therapeutic drug monitoring (TDM) in pediatric patients with neurofibromatosis type 1 (NF1) and plexiform neurofibromas (PN), assess interpatient pharmacokinetic variability, and explore the relationship between drug exposure, clinical response, and adverse effects.
Janka Kovács +8 more
wiley +1 more source
A Masked-Pre-Training-Based Fast Deep Image Prior Denoising Model
Applied SciencesCompared to supervised denoising models based on deep learning, the unsupervised Deep Image Prior (DIP) denoising approach offers greater flexibility and practicality by operating solely with the given noisy image.
Shuichen Ji +5 more
doaj +1 more source
A Model-Driven Deep Dehazing Approach by Learning Deep Priors
IEEE Access, 2021 Photos taken in hazy weather are usually covered with white masks and lose important details. Haze removal is a fundamental task and a prerequisite to many other vision tasks.
Dong Yang, Jian Sun
doaj +1 more source
FSRNet: End-to-End Learning Face Super-Resolution with Facial Priors
, 2017 Face Super-Resolution (SR) is a domain-specific super-resolution problem. The specific facial prior knowledge could be leveraged for better super-resolving face images.
Chen, Yu +4 more
core +1 more source
2024 IEEE International Conference on Computational Photography (ICCP)Phase-coded imaging is a computational imaging method designed to tackle tasks such as passive depth estimation and extended depth of field (EDOF) using depth cues inserted during image capture. Most of the current deep learning-based methods for depth estimation or all-in-focus imaging require a training dataset with high-quality depth maps and an ...
Shabtay, Nimrod +2 more
openaire +2 more sources
Early Stopping for Deep Image Prior
, 2021 Deep image prior (DIP) and its variants have showed remarkable potential for solving inverse problems in computer vision, without any extra training data. Practical DIP models are often substantially overparameterized. During the fitting process, these models learn mostly the desired visual content first, and then pick up the potential modeling and ...
Wang, Hengkang +5 more
openaire +2 more sources
Learning Deep Image Priors for Blind Image Denoising [PDF]
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2019 Image denoising is the process of removing noise from noisy images, which is an image domain transferring task, i.e., from a single or several noise level domains to a photo-realistic domain. In this paper, we propose an effective image denoising method by learning two image priors from the perspective of domain alignment.
Hou, Xianxu +7 more
openaire +2 more sources