Results 61 to 70 of about 25,441 (258)

Clinical Target Volume Auto-Segmentation of Esophageal Cancer for Radiotherapy After Radical Surgery Based on Deep Learning

Technology in Cancer Research & Treatment, 2021
Radiotherapy plays an important role in controlling the local recurrence of esophageal cancer after radical surgery. Segmentation of the clinical target volume is a key step in radiotherapy treatment planning, but it is time-consuming and operator ...
Ruifen Cao PhD, Xi Pei PhD, Ning Ge MD, Chunhou Zheng PhD   +3 more
doaj   +1 more source

DefectNET: multi-class fault detection on highly-imbalanced datasets

, 2019
As a data-driven method, the performance of deep convolutional neural networks (CNN) relies heavily on training data. The prediction results of traditional networks give a bias toward larger classes, which tend to be the background in the semantic ...
Anantrasirichai, N., Bull, David
core   +1 more source

Computational Modeling Meets 3D Bioprinting: Emerging Synergies in Cardiovascular Disease Modeling

Advanced Healthcare Materials, EarlyView.
Emerging advances in three‐dimensional bioprinting and computational modeling are reshaping cardiovascular (CV) research by enabling more realistic, patient‐specific tissue platforms. This review surveys cutting‐edge approaches that merge biomimetic CV constructs with computational simulations to overcome the limitations of traditional models, improve ...
Tanmay Mukherjee, Mehdi Salar Amoli, Sarah Rezapourdamanab, Lama Rita El Shammas, Martin L. Tomov, Emilio A. Mendiola, Vahid Serpooshan, Reza Avazmohammadi   +7 more
wiley   +1 more source

Why Dilated Convolutional Neural Networks: A Proof of Their Optimality

Entropy, 2021
One of the most effective image processing techniques is the use of convolutional neural networks that use convolutional layers. In each such layer, the value of the layer’s output signal at each point is a combination of the layer’s input signals ...
Jonatan Contreras, Martine Ceberio, Vladik Kreinovich   +2 more
doaj   +1 more source

Learning Dilation Factors for Semantic Segmentation of Street Scenes

, 2017
Contextual information is crucial for semantic segmentation. However, finding the optimal trade-off between keeping desired fine details and at the same time providing sufficiently large receptive fields is non trivial. This is even more so, when objects
DE Rumelhart, GJ Brostow, M Everingham, SR Richter, T-Y Lin   +4 more
core   +1 more source

Improving Abstractive Summarization via Dilated Convolution

Journal of Physics: Conference Series, 2020
AbstractIn this paper, a sequence-to-sequence based hybrid neural network model is proposed for abstractive summarization. Our method utilizes Bi-directional Long Short-Term Memory (Bi-LSTM) and multi-level dilated convolutions (MDC) to capture the global semantic information and semantic-unit level information, respectively.
Dawei Jin, Ruizhi Kang, Hongjun Zhang, Wening Hao, Gang Chen   +4 more
openaire   +1 more source

Simvastatin Restores Uteroplacental Hemodynamics and Trophoblast Function in Obstetric Antiphospholipid Syndrome in a Placenta‐on‐a‐Chip Model

Advanced Healthcare Materials, EarlyView.
Simvastatin mitigates placental hypoperfusion in OAPS by ameliorating abnormal uteromaternal hemodynamics and enhancing trophoblast invasion via optimized endothelial cell interactions under pathological shear stress, as evidenced by results from a placenta‐on‐a‐chip platform.
Hongli Liu, Yuan Wang, Yanjun Cai, Ruixin Guo, Shunhua Liu, Tingting Chen, Tingting Sun, Ruiheng Huo, Tengwei Liu, Qingfeng Lv, Xietong Wang   +10 more
wiley   +1 more source

Artificial Intelligence‐Assisted Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling

Advanced Materials, EarlyView.
AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll, Ivan Pinto‐Huguet, Enzo Rotunno, Thomas Galvani, Catalina Coll, Payam Habibzadeh Kavkani, Maria Chiara Spadaro, Yann‐Michel Niquet, Martin Børstad Eriksen, Sara Martí‐Sánchez, Georgios Katsaros, Giordano Scappucci, Peter Krogstrup, Giovanni Isella, Andreu Cabot, Gonzalo Merino, Pablo Ordejón, Stephan Roche, Vincenzo Grillo, Jordi Arbiol   +19 more
wiley   +1 more source

An efficient deep learning model for brain tumour detection with privacy preservation

CAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract Internet of medical things (IoMT) is becoming more prevalent in healthcare applications as a result of current AI advancements, helping to improve our quality of life and ensure a sustainable health system. IoMT systems with cutting‐edge scientific capabilities are capable of detecting, transmitting, learning and reasoning.
Mujeeb Ur Rehman, Arslan Shafique, Imdad Ullah Khan, Yazeed Yasin Ghadi, Jawad Ahmad, Mohammed S. Alshehri, Mimonah Al Qathrady, Majed Alhaisoni, Muhammad H. Zayyan   +8 more
wiley   +1 more source

Fundus-DANet: Dilated Convolution and Fusion Attention Mechanism for Multilabel Retinal Fundus Image Classification

Applied Sciences
The difficulty of classifying retinal fundus images with one or more illnesses present or missing is known as fundus multi-lesion classification. The challenges faced by current approaches include the inability to extract comparable morphological ...
Yang Yan, Liu Yang, Wenbo Huang
doaj   +1 more source