Medical Image Hybrid Watermark Algorithm Based on Frequency Domain Processing and Inception v3 by Yu Fan, Jingbing Li, Uzair Aslam Bhatti, Saqib Ali Nawaz, Yenwei Chen

“…The watermark extraction and decryption process relies on a key provided by a third party, enabling blind extraction of the watermark without requiring the original image. Through extensive experimental data analysis and comparisons with multiple existing algorithms, the results demonstrate that the proposed hybrid watermarking algorithm excels in terms of attack resistance and robustness, significantly improving the security and reliability of medical image watermarking.…”
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Integration of Hyperspectral Imaging and Deep Learning for Discrimination of Fumigated Lilies and Prediction of Quality Indicator Contents by Pengfei Zhang, Youyou Wang, Binbin Yan, Xiufu Wang, Zihua Zhang, Sheng Wang, Jian Yang

“…The CLSTM (convolutional neural network–long short-term memory) model, utilizing variable combination population analysis (VCPA) for wavelength selection, effectively differentiated sulfur fumigation patterns in lilies. …”
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Optimizing Tumor Detection in Brain MRI with One-Class SVM and Convolutional Neural Network-Based Feature Extraction by Azeddine Mjahad, Alfredo Rosado-Muñoz

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Semantically-Enhanced Feature Extraction with CLIP and Transformer Networks for Driver Fatigue Detection by Zhen Gao, Xiaowen Chen, Jingning Xu, Rongjie Yu, Heng Zhang, Jinqiu Yang

“…The trend is to train fatigue detection models using deep neural networks on driver video data, but challenges remain in coarse and incomplete high-level feature extraction and network architecture optimization. …”
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Domain Adaptation in Application to Gravitational Lens Finding by Hanna Parul, Sergei Gleyzer, Pranath Reddy, Michael W. Toomey

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Deep neural networks excel in COVID-19 disease severity prediction—a meta-regression analysis by Márton Rakovics, Fanni Adél Meznerics, Péter Fehérvári, Tamás Kói, Dezső Csupor, András Bánvölgyi, Gabriella Anna Rapszky, Marie Anne Engh, Péter Hegyi, Andrea Harnos

“…Neural Network-based tools have the highest performance with a pooled AUC of 0.893 (0.748–1.000), 0.752 (0.614–0.853) sensitivity, 0.914 (0.849–0.952) specificity, using clinical, laboratory, and imaging data. …”
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3DVT: Hyperspectral Image Classification Using 3D Dilated Convolution and Mean Transformer by Xinling Su, Jingbo Shao

“…Hyperspectral imaging and laser technology both rely on different wavelengths of light to analyze the characteristics of materials, revealing their composition, state, or structure through precise spectral data. …”
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PINNing cerebral blood flow: analysis of perfusion MRI in infants using physics-informed neural networks by Christoforos Galazis, Christoforos Galazis, Ching-En Chiu, Ching-En Chiu, Tomoki Arichi, Anil A. Bharath, Anil A. Bharath, Marta Varela, Marta Varela

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Maize Seed Variety Classification Based on Hyperspectral Imaging and a CNN-LSTM Learning Framework by Shuxiang Fan, Quancheng Liu, Didi Ma, Yanqiu Zhu, Liyuan Zhang, Aichen Wang, Qingzhen Zhu

“…This study introduced an efficient method for maize variety identification by combining hyperspectral imaging with a framework that integrates Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks. …”
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Development of an AI model for pneumothorax imaging: Dataset and model optimization strategies for real-world deployment by Wen-Chang Tseng, Yung-Cheng Wang, Wei-Chi Chen, Kang-Ping Lin

“…Image preprocessing involved normalization, data augmentation (rotation, translation, scaling, brightness adjustment), and standardization. …”
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Deep learning applications for human embryo assessment using time-lapse imaging: scoping review by Rawan AlSaad, Leen Abusarhan, Nour Odeh, Alaa Abd-alrazaq, Fadi Choucair, Rachida Zegour, Arfan Ahmed, Sarah Aziz, Javaid Sheikh

“…All studies utilized time-lapse video images (100%) as training data, while some also incorporated demographics, clinical and reproductive histories, and IVF cycle parameters. …”
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Constructing representative group networks from tractography: lessons from a dynamical approach by Eleanna Kritikaki, Matteo Mancini, Matteo Mancini, Diana Kyriazis, Natasha Sigala, Simon F. Farmer, Simon F. Farmer, Luc Berthouze

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“Infectious uveitis: a comprehensive systematic review of emerging trends and molecular pathogenesis using network analysis” by Muhammad Arif Asghar, Shixin Tang, Li Ping Wong, Peizeng Yang, Qinjian Zhao

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Unpaired Spatio-Temporal Fusion for Remote Sensing Images via Deformable Global-Local Feature Alignment by Xinlan Ding, Huihui Song, Xu Zhang

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Probing neuronal activity with genetically encoded calcium and voltage fluorescent indicators by Masayuki Sakamoto, Tatsushi Yokoyama

“…In recent years, these indicators have undergone significant developments, greatly enhancing the understanding of neural dynamics and networks. This review highlights the recent progress in genetically encoded calcium and voltage indicators and discusses the future direction of imaging techniques with big data analysis that deepens our understanding of the complexities of the brain.…”
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Artificial intelligence applied in identifying left ventricular walls in myocardial perfusion scintigraphy images: Pilot study. by Solange Amorim Nogueira, Fernanda Ambrogi B Luz, Thiago Fellipe O Camargo, Julio Cesar S Oliveira, Guilherme Carvalho Campos Neto, Felipe Brazao F Carvalhaes, Marcio Rodrigues C Reis, Paulo Victor Santos, Giovanna Souza Mendes, Rafael Maffei Loureiro, Daniel Tornieri, Viviane M Gomes Pacheco, Antonio Paulo Coimbra, Wesley Pacheco Calixto

“…This paper proposes the use of artificial intelligence techniques, specifically the nnU-Net convolutional neural network, to improve the identification of left ventricular walls in images of myocardial perfusion scintigraphy, with the objective of improving the diagnosis and treatment of coronary artery disease. …”
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Detection of hypertension from pharyngeal images using deep learning algorithm in primary care settings in Japan by Takeo Nakayama, Yusuke Tsugawa, Hiroshi Yoshihara, Memori Fukuda, Sho Okiyama

“…Pharyngeal images include vascular morphological information and may therefore be useful for identifying hypertension.Objectives This study sought to develop a deep learning-based artificial intelligence algorithm for identifying hypertension from pharyngeal images.Methods We conducted a secondary analysis of data from a clinical trial, in which demographic information, vital signs and pharyngeal images were obtained from patients with influenza-like symptoms in multiple primary care clinics in Japan. …”
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A robust deep learning framework for multiclass skin cancer classification by Burhanettin Ozdemir, Ishak Pacal

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3D Visualization System of Breast Magnetic Resonance Images Based on Deep Learning and Volume Rendering by Rong Chen, Stephen Karungaru, Kenji Terada, Changyan Xu

“…The multimodal feature fusion network (MFF-Vnet) based on the Vnet architecture employs a multi-branch design tailored to process multimodal images. …”
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EMI-LTI: An enhanced integrated model for lung tumor identification using Gabor filter and ROI by Jayapradha J, Su-Cheng Haw, Naveen Palanichamy, Kok-Why Ng, Muskan Aneja, Ammar Taiyab

“…Data augmentation is employed on the pre-processed images using two proposed architectures, namely (1) Convolutional Neural Network (CNN) and (2) Enhanced Integrated model for Lung Tumor Identification (EIM-LTI). • In this study, comparisons are made on non-pre-processed data, Haar and Gabor filters in CNN and the EIM-LTI models. …”
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