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Medical Physics
Scopus
ISSN 0094-2405 · Wiley · 7 artikel di indeks
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Artikel Jurnal Teks lengkap
Computer‐aided diagnosis in the era of deep learning
Computer-aided diagnosis (CAD) has been a major field of research for the past few decades. CAD uses machine learning methods to analyze imaging and/or nonimaging patient data and makes assessment of the patient's condition, which can then be used to assist clinicians in their decision-making…
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Artikel Jurnal
Low‐dose CT image and projection dataset
PURPOSE: To describe a large, publicly available dataset comprising computed tomography (CT) projection data from patient exams, both at routine clinical doses and simulated lower doses. ACQUISITION AND VALIDATION METHODS: The library was developed under local ethics committee approval. Projection…
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Artikel Jurnal Teks lengkap
Machine learning techniques for biomedical image segmentation: An overview of technical aspects and introduction to state‐of‐art applications
In recent years, significant progress has been made in developing more accurate and efficient machine learning algorithms for segmentation of medical and natural images. In this review article, we highlight the imperative role of machine learning algorithms in enabling efficient and accurate…
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Artikel Jurnal Teks lengkap
Report of AAPM Task Group 235 Radiochromic Film Dosimetry: An Update to TG‐55
The use of radiochromic film (RCF) dosimetry in radiation therapy is extensive due to its high level of achievable accuracy for a wide range of dose values and its suitability under a variety of measurement conditions. However, since the publication of the 1998 AAPM Task Group 55, Report No. 63 on…
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Artikel Jurnal Teks lengkap
Machine and deep learning methods for radiomics
Radiomics is an emerging area in quantitative image analysis that aims to relate large-scale extracted imaging information to clinical and biological endpoints. The development of quantitative imaging methods along with machine learning has enabled the opportunity to move data science research…
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Artikel Jurnal Teks lengkap
Toward data‐efficient learning: A benchmark for COVID‐19 CT lung and infection segmentation
PURPOSE: Accurate segmentation of lung and infection in COVID-19 computed tomography (CT) scans plays an important role in the quantitative management of patients. Most of the existing studies are based on large and private annotated datasets that are impractical to obtain from a single…
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Artikel Jurnal Teks lengkap
Principles and applications of multienergy CT: Report of AAPM Task Group 291
In x-ray computed tomography (CT), materials with different elemental compositions can have identical CT number values, depending on the mass density of each material and the energy of the detected x-ray beam. Differentiating and classifying different tissue types and contrast agents can thus be…