Results 81 to 90 of about 2,330,920 (308)

Learning Modality-Invariant Representations for Speech and Images

, 2017
In this paper, we explore the unsupervised learning of a semantic embedding space for co-occurring sensory inputs. Specifically, we focus on the task of learning a semantic vector space for both spoken and handwritten digits using the TIDIGITs and MNIST ...
Glass, James, Harwath, David, Leidal, Kenneth   +2 more
core   +1 more source

Detection of circulating tumor DNA in colorectal cancer patients using a methylation‐specific droplet digital PCR multiplex

Molecular Oncology, EarlyView.
We developed a cost‐effective methylation‐specific droplet digital PCR multiplex assay containing tissue‐conserved and tumor‐specific methylation markers. The assay can detect circulating tumor DNA with high accuracy in patients with localized and metastatic colorectal cancer.
Luisa Matos do Canto, Louise Raunkilde, Jan Lindebjerg, Mads Malik Aagaard, Christina Therkildsen, Jakob Kleif, Lars Henrik Jensen, Torben Frøstrup Hansen, Rikke Fredslund Andersen   +8 more
wiley   +1 more source

A Retinex-Based Variational Model for Enhancement and Restoration of Low-Contrast Remote-Sensed Images Corrupted by Shot Noise

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020
Remotely sensed images are widely used in many imaging applications. Images captured under adverse atmospheric conditions lead to degraded images that are contrast deficient and noisy.
I. P. Febin, P. Jidesh, A. A. Bini
doaj   +1 more source

Perspectives in educating molecular pathologists on liquid biopsy: Toward integrative, equitable, and decentralized precision oncology

Molecular Oncology, EarlyView.
Liquid biopsy enables minimally invasive, real‐time molecular profiling through analysis of circulating biomarkers in biological fluids. This Perspective highlights the importance of training pathologists through integrative educational programs, such as the European Masters in Molecular Pathology, to ensure effective and equitable implementation of ...
Marius Ilié, Umberto Malapelle, Catherine Alix‐Panabières, Claus Lindbjerg Andersen, Sandra Chlebowski, Vivien Lake, Caroline Lacoux, Virginie Lespinet‐Fabre, Olivier Bordone, Simon Heeke, Christophe Bontoux, Ellen Heitzer, Klaus Pantel, Paul Hofman   +13 more
wiley   +1 more source

V‐UNet: Medical Image Segmentation Based on Variational Attention Mechanism

CAAI Transactions on Intelligence Technology
Accurate medical image segmentation plays a crucial role in improving the precision of computer‐aided diagnosis. However, complex boundary shapes, low contrast and blurred anatomical structures make fine‐grained segmentation a challenging task ...
Yang Zhang, Qiang Yang, Tian Li, Fanghong Zhang, Yu Ren, Yinhao Li, Chuanyun Xu   +6 more
doaj   +1 more source

Location Dependent Dirichlet Processes

, 2017
Dirichlet processes (DP) are widely applied in Bayesian nonparametric modeling. However, in their basic form they do not directly integrate dependency information among data arising from space and time.
A Oliva, A Rodríguez, C Bishop, C Williams, CE Rasmussen, D Blei, D Blei, D Dunson, E Sudderth, F Zhu, H Ishwaran, J Duan, J Griffin, J Griffin, J Paisley, J Sethuraman, J Shi, L Ren, N Foti, P Orbanz, R Unnikrishnan, S Kumar, T Ferguson, X Sun, YW Teh   +24 more
core   +1 more source

Next‐generation proteomics improves lung cancer risk prediction

Molecular Oncology, EarlyView.
This is one of very few studies that used prediagnostic blood samples from participants of two large population‐based cohorts. We identified, evaluated, and validated an innovative protein marker model that outperformed an established risk prediction model and criteria employed by low‐dose computed tomography in lung cancer screening trials.
Megha Bhardwaj, Clara Frick, Ben Schöttker, Bernd Holleczek, Hermann Brenner   +4 more
wiley   +1 more source

Image denoising by a direct variational minimization

EURASIP Journal on Advances in Signal Processing, 2011
In this article we introduce a novel method for the image de-noising which combines a mathematically well-posdenes of the variational modeling with the efficiency of a patch-based approach in the field of image processing.
Pilipović Stevan, Janev Marko, Atanacković Teodor, Obradović Radovan   +3 more
doaj  

Image processing with Optical matrix vector multipliers implemented for encoding and decoding tasks

Light: Science & Applications
This study introduces an optical neural network (ONN)-based autoencoder for efficient image processing, utilizing specialized optical matrix-vector multipliers for both encoding and decoding tasks.
Minjoo Kim, Yelim Kim, Won Il Park
doaj   +1 more source

A variational joint segmentation and registration framework for multimodal images

Journal of Algorithms & Computational Technology, 2020
Image segmentation and registration are closely related image processing techniques and often required as simultaneous tasks. In this work, we introduce an optimization-based approach to a joint registration and segmentation model for multimodal images ...
Adela Ademaj, Lavdie Rada, Mazlinda Ibrahim, Ke Chen   +3 more
doaj   +1 more source