PyTomography: A python library for medical image reconstruction by Lucas A. Polson, Roberto Fedrigo, Chenguang Li, Maziar Sabouri, Obed Dzikunu, Shadab Ahamed, Nicolas Karakatsanis, Sara Kurkowska, Peyman Sheikhzadeh, Pedro Esquinas, Arman Rahmim, Carlos Uribe

“…Its flexible and modular design decouples system matrices, likelihoods, and reconstruction algorithms, simplifying the process of integrating new imaging modalities using various python tools. …”
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Magnetic resonance imaging of cruciate ligament disorders: current updates by Tanda Yang, Yexin Li, Longtao Yang, Qian Liu

“…While conventional structural magnetic resonance imaging (MRI) can detect cruciate ligament anatomy and injuries, it has inherent limitations. …”
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Research on Automatic Dodging Method for Road Surface Line Array Images by Fuqiang Yang, Jiabin Zhao, Bo Yu, Jiayuan Zhang, Wei Tang

“…To eliminate the impact of image greyscale unevenness on subsequent processing, an automatic dodging method is proposed based on mask dodging algorithm. …”
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Reversible image steganography based on residual structure and attention mechanism by Lianshan Liu, Shanshan Tong, Qianwen Xue

“…Abstract Image steganography is a process of embedding a secret image into a cover image to achieve secret transmission and accurately recovering a secret image from a stego image. …”
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KEDM: Knowledge-Embedded Diffusion Model for Infrared Image Destriping by Lingxiao Li, Xin Wang, Dan Huang, Yunan He, Zhuqiang Zhong, Qingling Xia

“…Meanwhile, DWCM uses wavelet convolution operations to construct prior loss functions for stripe noise, precisely guiding the diffusion reconstruction process to achieve a clean, stripe-free image. Empirical evaluations on several benchmark datasets demonstrate that the proposed KEDM outperforms other state-of-the-art destriping algorithms in terms of visual quality and quantitative metrics, validating its excellent performance.…”
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Illumination-adaptative granularity progressive multimodal image fusion method by Chuanyun WANG, Dongdong SUN, Mingqi ZHOU, Tian WANG, Qian GAO, Zhaokui LI

“…The processed scene vectors are then progressively embedded into the fusion image reconstruction network, providing the fusion model with the ability to perceive scene information. …”
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CNN–Transformer Hybrid Architecture for Underwater Sonar Image Segmentation by Juan Lei, Huigang Wang, Zelin Lei, Jiayuan Li, Shaowei Rong

“…However, the existing SOD algorithms find it difficult to effectively extract salient features and spatial structure information from images with scarce semantic information, uneven intensity distribution, and high noise. …”
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Multi-Objective Robust Optimization Reconstruction Algorithm for Electrical Capacitance Tomography by Xuejie Yang, Jing Lei, Qibin Liu

“…Qualitative and quantitative evaluation results demonstrate that the proposed method surpasses mainstream imaging algorithms, enhancing the automation level of the reconstruction process and image quality while exhibiting exceptional robustness. …”
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Tumor segmentation in whole-slide histology images using deep learning by V. A. Kovalev, V. A. Liauchuk, A. A. Kalinovski, M. V. Fridman

“…The resultant probability maps were post-processed using conventional image processing algorithms to obtain the final binary masks of pathological regions. …”
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Automated LoD-3 Reconstruction Using Oblique UAV Images by H. S. Kim, J. Carpenter, J. Jung

“…Based on the photogrammetry, cameras are simulated to generate facade images of buildings. The YOLOv5-based window detection is followed using these simulated images. …”
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Multi-label semantic segmentation of magnetic resonance images of the prostate gland by Mark Locherer, Christopher Bonenberger, Wolfgang Ertel, Boris Hadaschik, Kristina Stumm, Markus Schneider, Jan Philipp Radtke

“…We present a data processing pipeline consisting of a cascaded network architecture that is able to perform multi-label semantic segmentation, hence, capable of classifying each pixel in a $$\textrm{T}_{2}$$ T 2 -weighted image not only to one class but to a subset of the prostate zones and classes of interest. …”
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Study of methods for extracting contours of objects on raster images of amber samples by Yu.O. Podchashynskyi, A.V. Ryzhuk

“…The effective operation of the TVS requires the development of methods and algorithms for processing raster images of objects, taking into account their features for the applied field of the TVS application. …”
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Manifold mesh reconstruction from dense matching points of oblique images by Weichen Sun, Chenxi Duan, Yunhua Zhao, Lei Han

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Adaptive Fast Refocusing for Ship Targets With Complex Motion in SAR Images by Xinqi Xu, Xiangguang Leng, Zhongzhen Sun, Xiangdong Tan, Kefeng Ji, Gangyao Kuang

“…This algorithm can adaptively adjust algorithm parameters based on SAR images from different SAR platforms, thereby more accurately determining the optimal rotation interval (ORI), reducing computational cost, and achieving adaptive fast refocusing. …”
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Aircraft Position Estimation Using Deep Convolutional Neural Networks for Low SNR (Signal-to-Noise Ratio) Values by Przemyslaw Mazurek, Wojciech Chlewicki

“…In the learning process, a database of actual aircraft images was used. …”
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Classification of Cavendish Banana Quality using Convolutional Neural Network by Ajeng Ayu Suryani, Ummi Athiyah, Yohani Setiya Rafika Nur, Warto

“…The results indicate the effectiveness of the confusion matrix in identifying training data and detecting images. It can be concluded that using more training data leads to higher accuracy, as fewer image reading errors occur when fewer images are processed. …”
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easyspec: An Open-source Python Package for Long-slit Spectroscopy by Raniere de Menezes, Francesco Massaro, Michela Negro, Claudia M. Raiteri, Harold Peña-Herazo, Jose A. Acosta-Pulido

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Radiomic Feature Extraction Based on Computed Tomography for Stroke Patients by Alamgir Hossain, Jolly Sultana, Shahed Hossain, Hafizur Rahman

“…Conclusion: In summary, stroke imaging analysis benefits greatly from the deployment of complex image processing techniques, reliable feature extraction methods, and cutting-edge segmentation algorithms. …”
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Deep learning based detection of silicosis from computed tomography images by Hamit Aksoy, Ümit Atila, Sertaç Arslan

“…The automated detection and recognition of silicosis in lung computed tomography (CT) images can be considered the backbone of assisting the silicosis diagnosis process. …”
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CONSTRUCTING METAMORPHOSIS OF IMAGES FOR THE OBJECTS ON THE BASIS OF SOLVING EULER-POINCARE EQUATIONS by S. V. Leichter

“…The designed algorithms can be used through a biometrical system, in images and subjects classification systems, machine vision systems, images and patterns recognition, tracking systems.…”
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