Thalamic volume differentiates multiple sclerosis from neuromyelitis optica spectrum disorder: MRI-based retrospective study by Manal Alosaimi, Hatham Alkanhal, Saleh Aldeligan, Nuha Alkhawajah, Alaa Albishi, Bander Hilabi, Salman Aljarallah

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Is the Adventitial Vasa Vasorum in Vulnerable Carotid Plaques Increased or Decreased? by Wang Yixuan, Jin Lin, Chen Jianxiong, Yang Huixian, Shen Cuiqin, Xu Wenzhe, Shen Yuzhou, Huang Jun, Sun Liwan, Du Lianfang, Wang Bei, Li Fan, Li Zhaojun

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Advanced deep learning techniques for recognition of dental implants by Veena Benakatti, Ramesh P. Nayakar, Mallikarjun Anandhalli, Rohit sukhasare

“…Optimizing this model for a balance between accuracy and efficiency will be necessary for real-time medical imaging applications.…”
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Artificial intelligence in precision medicine for lung cancer: A bibliometric analysis by Yuchai Wang, Weilong Zhang, Xiang Liu, Li Tian, Wenjiao Li, Peng He, Sheng Huang, Fuyuan He, Xue Pan

“…These publications were mainly published in the following scientific disciplines, including Radiology Nuclear Medicine, Medical Imaging, Oncology, and Computer Science Notably, Li Weimin and Aerts Hugo J. …”
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Uncertainty-aware deep learning in healthcare: A scoping review. by Tyler J Loftus, Benjamin Shickel, Matthew M Ruppert, Jeremy A Balch, Tezcan Ozrazgat-Baslanti, Patrick J Tighe, Philip A Efron, William R Hogan, Parisa Rashidi, Gilbert R Upchurch, Azra Bihorac

“…Among 30 included studies, 24 described medical imaging applications. All imaging model architectures used convolutional neural networks or a variation thereof. …”
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Financing healthcare services: a qualitative assessment of private health insurance schemes in Ghana by Angela Asante, Richard A. Bonney, Peter Twum

“…Benefit packages varied, with distinct plans like the “X-scan plan” for medical imaging. Payment structures ranged from upfront payments to flexible options. …”
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Machine learning-based myocardial infarction bibliometric analysis by Ying Fang, Yuedi Wu, Lijuan Gao

“…CiteSpace was used for temporal trend analysis, Bibliometrix for quantitative country and institutional analysis, and VOSviewer for visualization of collaboration networks.ResultsSince the emergence of research literature on medical imaging and machine learning (ML) in 2008, interest in this field has grown rapidly, particularly since the pivotal moment in 2016. …”
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A multi-patch-based deep learning model with VGG19 for breast cancer classifications in the pathology images by Anitha Ponraj, Palanigurupackiam Nagaraj, Duraisamy Balakrishnan, Parvathaneni Naga Srinivasu, Jana Shafi, Wonjoon Kim, Muhammad Fazal Ijaz

“…Given the complexity of breast tissues, effective detection and classification of breast cancer is crucial in medical imaging. This study introduces a novel method, MPa-DCAE, which uses a multi-patch-based deep convolutional auto-encoder (DCAE) framework combined with VGG19 to detect and classify breast cancer in histopathology images. …”
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An Analysis of the Rate and Reasons for Rejected Radiographs in Emergency and Non-Emergency Radiology Departments in Yasuj, Iran by Seyyed Amir Moradian, Hamed Zamani, Saman Dalvand

“…Materials and Methods: This cross-sectional study was carried out over 14 days in Yasuj, Iran, in the accident and emergency (round-the-clock) and non-emergency (day) medical imaging departments. In terms of quality, a total of 7,006 images were classified into the following three grades; A (Good), B (Fair), and C (rejected). …”
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Genistein Implications in Radiotherapy: Kill Two Birds with One Stone by Xiongxiong Liu, Tong Zheng, Yanyu Bao, Ping Li, Ting Zhao, Yan Liu, Hui Wang, Chao Sun

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ESTIMATION OF ENTRANCE SURFACE DOSE (ESD) AS A DOSE PROFILE FOR PATIENTS UNDERGOING RADIOGRAPHY EXAMINATION BASED ON TUBE OUTPUT MEASUREMENT by Risalatul Latifah, Muhammad Rosyid, Firdy Yuana, Achmad Hidayat

“…Background: Radiography examinations are the most widely used and indispensable tools in medical imaging. The dose received by the patient should be known to prevent the risk of radiation exposure. …”
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Systematic review of 99 extremity bone malignancy survival prediction models by Cheng-Yo Lai, Hung-Kuan Yen, Hao-Chen Lin, Olivier Quinten Groot, Wei-Hsin Lin, Hao-Ping Hsu

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Transcriptomic and metabolomic analyses reveal the spatial role of carnitine metabolism in the progression of hepatitis B virus cirrhosis to hepatocellular carcinoma by Pengxiang Gao, Qiuping Liu, Ziye Luo, Wenjun Pu, Wenjun Pu

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Magnetic resonance imaging in primates. The example of the mouse lemur (Microcebus murinus): From detection of pathological aging to therapeutic evaluations by Nelly Joseph-Mathurin, Olene Dorieux, Audrey Kraska, Anne Bertrand, Mathieu Santin, Nadine El Tannir El Tayara, Marc Dhenain

“…Indeed several animals develop age-associated cerebral alterations like amyloidosis and other cerebral changes. Non invasive medical imaging methods such as magnetic resonance imaging (MRI) can be used to follow-up brain changes in these animals. …”
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Breast Cancer Knowledge and Practice of Breast Self-Examination among Female University Students, Gaza by Samira S. Abo Al-Shiekh, Mohamed Awadelkarim Ibrahim, Yasser S. Alajerami

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Cystic Echinococcosis/Hydatid Cyst Coinfection with HIV: A Report from Shiraz, Iran by Yosef Sharifi, Seyed Mahmoud Sadjjadi, Hamed Nikoupour Dailami, Seyed Hamed Jafari, Mohammad Hossein Anbardar, Mohammad Bagher Khosravi

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The Venus score for the assessment of the quality and trustworthiness of biomedical datasets by Davide Chicco, Alessandro Fabris, Giuseppe Jurman

“…We apply the Venus score to twelve datasets from multiple subdomains, including electronic health records, medical imaging, microarray and bulk RNA-seq gene expression, cheminformatics, physiologic electrogram signals, and medical text. …”
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Classification of white blood cells (leucocytes) from blood smear imagery using machine and deep learning models: A global scoping review. by Rabia Asghar, Sanjay Kumar, Arslan Shaukat, Paul Hynds

“…Likewise, it is critical that future health professionals be made aware of the power, efficacy, precision and applicability of computer science, soft computing and artificial intelligence contributions to medicine, and particularly in areas like medical imaging.…”
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Technical Considerations of Phosphorous-32 Bremsstrahlung SPECT Imaging after Radioembolization of Hepatic Tumors: A Clinical Assessment with a Review of Imaging Parameters by Elahe Pirayesh, Mahasti Amoui, Shahram Akhlaghpoor, Shahnaz Tolooee, Maryam Khorrami, Hossain PoorBeigi, Shahab Sheibani, Majid Assadi

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Enhancing Cervical Cancer Classification: Through a Hybrid Deep Learning Approach Integrating DenseNet201 and InceptionV3 by Abhiram Sharma, R. Parvathi

“…Future research will focus on further improving the system’s performance and investigating its applicability to other medical imaging tasks. The proposed model is expected to contribute significantly to early and accurate cervical cancer diagnosis, enhancing patient outcomes and supporting healthcare professionals in clinical decision-making.…”
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