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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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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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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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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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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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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A pilot study comparing three-dimensional models of tumor histopathology and magnetic resonance imaging by Anne Koivuholma, Heli J. Sistonen, Katri Aro, Antti Mäkitie, Jaana Hagström, Timo Atula

“…This has become an everyday tool especially in medical imaging. However, modeling soft tissue histopathology in 3D is in its early stages, thus making 3D comparison between radiology and histopathology difficult. …”
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Advances in Biomedical Missing Data Imputation: A Survey by Miriam Barrabes, Maria Perera, Victor Novelle Moriano, Xavier Giro-I-Nieto, Daniel Mas Montserrat, Alexander G. Ioannidis

“…This survey paper provides a comprehensive overview of the extensive literature on missing data imputation techniques, with a specific focus on applications in genomics, single-cell RNA sequencing, health records, and medical imaging. We outline the fundamental principles underlying each imputation technique and present a detailed analysis of their advantages and disadvantages, categorized by missing data patterns. …”
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Bayesian deep learning applied to diabetic retinopathy with uncertainty quantification by Masoud Muhammed Hassan, Halbast Rashid Ismail

“…Deep Learning (DL) has significantly contributed to the field of medical imaging in recent years, leading to advancements in disease diagnosis and treatment. …”
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Modified AlexNet Convolution Neural Network For Covid-19 Detection Using Chest X-ray Images by Shadman Q. Salih, Hawre Kh. Abdulla, Zanear Sh. Ahmed, Nigar M. Shafiq Surameery, Rasper Dh. Rashid

“…In the last decade, medical imaging techniques show its efficiency in helping radiologists to detect and diagnose the diseases. …”
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Metastatic Malignant Ectomesenchymoma Initially Presenting as a Pelvic Mass: Report of a Case and Review of Literature by A. Nael, P. Siaghani, W. W. Wu, K. Nael, Lisa Shane, S. G. Romansky

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Multiomics Integrated Analysis Identifies SLC24A2 as a Potential Link between Type 2 Diabetes and Cancer by Qin Bian, Haijun Li, Xiaoyi Wang, Tingting Liang, Kai Zhang

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Giant Hydatid Cyst Originating From Psoas Muscle Extending to the Iliac Bone: A Case Report by Mohammad Hadi Niakan, Fatemeh Mirparsa, Hamid Zaferani Arani, Sedighe Hooshmandi, Elham Peyravi

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