Results 1 to 10 of about 9,200 (172)

CycleGan-based kV-to-MV image translation for potential in vivo dosimetry application: concept proposal and cross-institutional validation [PDF]

BMC Medical Imaging
Background This work aims to develop and validate a novel CycleGan-based methodology to transfer the kV planning CT (pCT) to the reference MV portal images, potentially applicable to in vivo treatment dose monitoring.
Rui Qu, Zhexiang Song, Qijian Lu, Huimin Hu, Zhengkun Dong, Shutong Yu, Jiang Liu, Juan Deng, Guojian Mei, Chuou Yin, Qiao Li, Fei Xiang, Tian Li, Chen Lin, Junfeng Qi, Xiaoyun Le, Yibao Zhang   +16 more
doaj   +2 more sources

Local Binary Pattern–Cycle Generative Adversarial Network Transfer: Transforming Image Style from Day to Night [PDF]

Journal of Imaging
Transforming images from day style to night style is crucial for enhancing perception in autonomous driving and smart surveillance. However, existing CycleGAN-based approaches struggle with texture loss, structural inconsistencies, and high computational
Abeer Almohamade, Salma Kammoun, Fawaz Alsolami   +2 more
doaj   +2 more sources

Reciprocal style and information transfer between historical Istanbul Pervititch Maps and satellite views using machine learning

ESTOA: Revista de la Facultad de Arquitectura y Urbanismo de la Universidad de Cuenca, 2022
Historical maps contain significant data on the cultural, social, and urban character of cities. However, most historical maps utilize specific notation methods that differ from those commonly used today and converting these maps to more recent formats ...
Sema Alaçam, Ilker Karadag, Orkan Zeynel Güzelci   +2 more
doaj   +1 more source

A Diverse Domain Generative Adversarial Network for Style Transfer on Face Photographs

International Journal of Interactive Multimedia and Artificial Intelligence, 2022
The applications of style transfer on real time photographs are very trending now. This is used in various applications especially in social networking sites such as SnapChat and beauty cameras.
Rabia Tahir, Keyang Cheng, Bilal Ahmed Memon, Qing Liu   +3 more
doaj   +1 more source

Automated Extraction of Cerebral Infarction Region in Head MR Image Using Pseudo Cerebral Infarction Image by CycleGAN

Applied Sciences, 2022
Since recognizing the location and extent of infarction is essential for diagnosis and treatment, many methods using deep learning have been reported. Generally, deep learning requires a large amount of training data.
Mizuki Yoshida, Atsushi Teramoto, Kohei Kudo, Shoji Matsumoto, Kuniaki Saito, Hiroshi Fujita   +5 more
doaj   +1 more source

An efficient ECG denoising method by fusing ECA-Net and CycleGAN

Mathematical Biosciences and Engineering, 2023
For wearable electrocardiogram (ECG) acquisition, it was easy to infer motion artifices and other noises. In this paper, a novel end-to-end ECG denoising method was proposed, which was implemented by fusing the Efficient Channel Attention (ECA-Net) and ...
Peng Zhang , Mingfeng Jiang , Yang Li, Ling Xia, Zhefeng Wang, Yongquan Wu, Yaming Wang, Huaxiong Zhang   +7 more
doaj   +1 more source

Multi-Contrast MRI Image Synthesis Using Switchable Cycle-Consistent Generative Adversarial Networks

Diagnostics, 2022
Multi-contrast MRI images use different echo and repetition times to highlight different tissues. However, not all desired image contrasts may be available due to scan-time limitations, suboptimal signal-to-noise ratio, and/or image artifacts.
Huixian Zhang, Hailong Li, Jonathan R. Dillman, Nehal A. Parikh, Lili He   +4 more
doaj   +1 more source

Frequency-Domain-Based Structure Losses for CycleGAN-Based Cone-Beam Computed Tomography Translation

Sensors, 2023
Research exploring CycleGAN-based synthetic image generation has recently accelerated in the medical community due to its ability to leverage unpaired images effectively.
Suraj Pai, Ibrahim Hadzic, Chinmay Rao, Ivan Zhovannik, Andre Dekker, Alberto Traverso, Stylianos Asteriadis, Enrique Hortal   +7 more
doaj   +1 more source

Image Translation by Ad CycleGAN for COVID-19 X-Ray Images: A New Approach for Controllable GAN

Sensors, 2022
We propose a new generative model named adaptive cycle-consistent generative adversarial network, or Ad CycleGAN to perform image translation between normal and COVID-19 positive chest X-ray images.
Zhaohui Liang, Jimmy Xiangji Huang, Sameer Antani   +2 more
doaj   +1 more source

Map-Guided Curriculum Domain Adaptation and Uncertainty-Aware Evaluation for Semantic Nighttime Image Segmentation

, 2021
We address the problem of semantic nighttime image segmentation and improve the state-of-the-art, by adapting daytime models to nighttime without using nighttime annotations.
Dai, Dengxin, Sakaridis, Christos, Van Gool, Luc   +2 more
core   +2 more sources