The Impact of Weighting Factors on Dual-Energy Computed Tomography Image Quality in Non-Contrast Head Examinations: Phantom and Patient Study by Doris Šegota Ritoša, Doris Dodig, Slavica Kovačić, Nina Bartolović, Ivan Brumini, Petra Valković Zujić, Slaven Jurković, Damir Miletić

“…<b>Results</b>: Quantitative phantom image analysis revealed the best gray-to-white matter contrast-to-noise ratio (CNR) at the highest WFs and minimal noise artifacts at the lowest WF values. …”
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Automatic Detection of the Aortic Annular Plane and Coronary Ostia from Multidetector Computed Tomography by Patricio Astudillo, Peter Mortier, Johan Bosmans, Ole De Backer, Peter de Jaegere, Francesco Iannaccone, Matthieu De Beule, Joni Dambre

“…Furthermore, a high correlation is observed between predicted and manually measured coronary heights (for both R2 = 0.8). The image analysis time per patient was below one second. …”
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Ventricular function assessment using an ultrafast spoiled gradient echo sequence with an intravascular blood pool contrast agent in pediatric patients. by Tayaba Miah, Rithvik Gunda, Gerald Greil, Mohammad Hussain, Qing Zou

“…Image quality assessment via expert subjective image analysis scores is consistent with the data. All Bland-Altman plots show good agreement and reveal no systematic bias or random error.…”
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Microscopic Analysis of Temperature Effects on Surface Colonization and Biofilm Morphology of <i>Salmonella enterica</i> by Zachariah Vice, You Zhou, Sapna Chitlapilly Dass, Rong Wang

“…We developed methods using scanning electron microscopy and confocal microscopy with a novel image analysis software tool to investigate the temperature influence on <i>S. enterica</i> cell colonization and biofilm formation by directly visualizing and comparing the biofilm matrix’s morphological differences under various temperatures. …”
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MCPA: multi-scale cross perceptron attention network for 2D medical image segmentation by Liang Xu, Mingxiao Chen, Yi Cheng, Pengwu Song, Pengfei Shao, Shuwei Shen, Peng Yao, Ronald X. Xu

“…Abstract The UNet architecture, based on convolutional neural networks (CNN), has demonstrated its remarkable performance in medical image analysis. However, it faces challenges in capturing long-range dependencies due to the limited receptive fields and inherent bias of convolutional operations. …”
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Deep Image Synthesis, Analysis and Indexing Using Integrated CNN Architectures by Muhammad Arslan, Muhammad Asad, Ali Haider Khan, Sajid Iqbal, Muhammad Nabeel Asghar, Abdullah Abdulrhman Alaulamie

“…The proposed model presents a three-phase approach including image analysis, synthesis, and indexing to improve image retrieval efficiency and accuracy by integrating deep features of CNN models. …”
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A Fine-Grained Aircraft Target Recognition Algorithm for Remote Sensing Images Based on YOLOV8 by Xiao-Nan Jiang, Xiang-Qian Niu, Fan-Lu Wu, Yao Fu, He Bao, Yan-Chao Fan, Yu Zhang, Jun-Yan Pei

“…Fine-grained recognition plays a pivotal role in the field of remote sensing image analysis, particularly in critical applications such as reconnaissance and early warning, intelligence analysis, and intelligent interpretation. …”
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Reproducibility and repeatability of 18F-(2S, 4R)-4-fluoroglutamine PET imaging in preclinical oncology models. by Gregory D Ayers, Allison S Cohen, Seong-Woo Bae, Xiaoxia Wen, Alyssa Pollard, Shilpa Sharma, Trey Claus, Adria Payne, Ling Geng, Ping Zhao, Mohammed Noor Tantawy, Seth T Gammon, H Charles Manning

“…Three individuals analyzed the tumor uptake of 18F-Gln using the same set of images, the same image analysis software, and the same analysis method. …”
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Long-Term Evaluation of Capsulotomy Shape and Posterior Capsule Opacification after Low-Energy Bimanual Femtosecond Laser-Assisted Cataract Surgery by Tommaso Verdina, Chiara Peppoloni, Lucrezia Barbieri, Maria Rosaria Carbotti, Bruno Battaglia, Rodolfo Mastropasqua, Gian Maria Cavallini

“…A digital image of the capsule with slit-lamp retroillumination was performed in all patients at 18 months of follow-up. Image analysis software (ImageJ) was used to evaluate the shape of the capsulotomy in terms of diameter, area, and circularity. …”
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Evaluating pre-processing and deep learning methods in medical imaging: Combined effectiveness across multiple modalities by Thien B. Nguyen-Tat, Tran Quang Hung, Pham Tien Nam, Vuong M. Ngo

“…Advanced computational techniques, particularly preprocessing methods and deep learning models, have demonstrated significant potential for improving medical image analysis. However, determining the optimal combination of these techniques across different types of medical images remains a challenge. …”
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An AI-Based Digital Scanner for <i>Varroa destructor</i> Detection in Beekeeping by Daniela Scutaru, Simone Bergonzoli, Corrado Costa, Simona Violino, Cecilia Costa, Sergio Albertazzi, Vittorio Capano, Marko M. Kostić, Antonio Scarfone

“…The device works through image analysis of a sticky sheet previously placed under the beehive for some days, intercepting the Varroa mites that naturally fall. …”
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Automatic morphology phenotyping of tetra- and hexaploid wheat spike using computer vision methods by A. Yu. Pronozin, A. A. Paulish, E. A. Zavarzin, A. Yu. Prikhodko, N. M. Prokhoshin, Yu. V. Kruchinina, N. P. Goncharov, E. G. Komyshev, M. A. Genaev

“…The traits were obtained as a result of image analysis using the WERecognizer program. A cluster analysis of plants according to the characteristics of the spike shape and comparison of their distributions in tetraploid and hexaploid species showed a higher variability of traits in hexaploid species compared to tetraploid ones. …”
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Universal conditional networks (UniCoN) for multi-age embryonic cartilage segmentation with Sparsely annotated data by Nishchal Sapkota, Yejia Zhang, Zihao Zhao, Maria Jose Gomez, Yuhan Hsi, Jordan A. Wilson, Kazuhiko Kawasaki, Greg Holmes, Meng Wu, Ethylin Wang Jabs, Joan T. Richtsmeier, Susan M. Motch Perrine, Danny Z. Chen

“…These results highlight the potential of our approach for developing robust, universal models capable of handling diverse datasets with limited annotated data, a key challenge in DL-based medical image analysis.…”
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Bone scan images dataset for study of bone metastases in adult breast cancer patients at IICS-UNA, ParaguayZenodo by Carolina Elizabeth Villegas-Colmán, Julio César Mello-Román, José Luis Vázquez Noguera, Horacio Legal-Ayala, Pastor Pérez Estigarribia, Benicio Grossling-Vallejos, Ronald Rivas, María Gloria Pedrozo, Cynthia Duarte, Graciela Giménez, Andrés Uldera, Marina Arnal, Nicole Barreto, Teresa Rojas

“…This dataset will be helpful for researchers working on bone scan image analysis using artificial intelligence techniques to classify bone metastases.…”
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Prospects of two-port vitrectomy in the treatment of patients with epiretinal fibrosis by D.V. Borisova, I.A. Frolychev, N.A. Pozdeeva

“…Op tical coherence tomography with retinal image analysis was used to assess the recovery of anatomical parameters. …”
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Optical Coherence Tomography Angiography to Distinguish Changes of Choroidal Neovascularization after Anti-VEGF Therapy: Monthly Loading Dose versus Pro Re Nata Regimen by Alexandra Miere, Hassiba Oubraham, Francesca Amoroso, Pauline Butori, Polina Astroz, Oudy Semoun, Elsa Bruyere, Alexandre Pedinielli, Manar Addou-Regnard, Camille Jung, Salomon Y. Cohen, Eric H. Souied

“…CNV size was measured using a free image analysis software (ImageJ, open-source imaging processing software, 2.0.0). …”
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BenthicNet: A global compilation of seafloor images for deep learning applications by Scott C. Lowe, Benjamin Misiuk, Isaac Xu, Shakhboz Abdulazizov, Amit R. Baroi, Alex C. Bastos, Merlin Best, Vicki Ferrini, Ariell Friedman, Deborah Hart, Ove Hoegh-Guldberg, Daniel Ierodiaconou, Julia Mackin-McLaughlin, Kathryn Markey, Pedro S. Menandro, Jacquomo Monk, Shreya Nemani, John O’Brien, Elizabeth Oh, Luba Y. Reshitnyk, Katleen Robert, Chris M. Roelfsema, Jessica A. Sameoto, Alexandre C. G. Schimel, Jordan A. Thomson, Brittany R. Wilson, Melisa C. Wong, Craig J. Brown, Thomas Trappenberg

“…A large deep learning model was trained on this compilation and preliminary results suggest it has utility for automating large and small-scale image analysis tasks. The compilation and model are made openly available for reuse.…”
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A ‘torn bag mechanism’ of small extracellular vesicle release via limiting membrane rupture of en bloc released amphisomes (amphiectosomes) by Tamás Visnovitz, Dorina Lenzinger, Anna Koncz, Péter M Vizi, Tünde Bárkai, Krisztina V Vukman, Alicia Galinsoga, Krisztina Németh, Kelsey Fletcher, Zsolt I Komlósi, Csaba Cserép, Ádám Dénes, Péter Lőrincz, Gábor Valcz, Edit I Buzas

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Multiparametric MRI and artificial intelligence in predicting and monitoring treatment response in bladder cancer by Yuki Arita, Thomas C. Kwee, Oguz Akin, Keisuke Shigeta, Ramesh Paudyal, Christian Roest, Ryo Ueda, Alfonso Lema-Dopico, Sunny Nalavenkata, Lisa Ruby, Noam Nissan, Hiromi Edo, Soichiro Yoshida, Amita Shukla-Dave, Lawrence H. Schwartz

“…In comparison to the current Response Evaluation Criteria in Solid Tumors (RECIST), QIBs and mpMRI-based radiomics, in combination with artificial intelligence (AI)-based image analysis, may potentially allow for earlier identification of therapy-induced tumor changes. …”
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Ultra-low dose dual-layer detector spectral CT for pulmonary nodule screening: image quality and diagnostic performance by Li Ding, Mingwang Chen, Xiaomei Li, Yuting Wu, Jingxu Li, Shuting Deng, Yikai Xu, Zhao Chen, Chenggong Yan

“…Quantitative and qualitative image analysis, nodule detectability, and Lung-RADS evaluation were compared using repeated one-way analysis of variance, Friedman test, and weighted kappa coefficient. …”
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