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230811 ||| eng |
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|a 9783036550145
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|a books978-3-0365-5014-5
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|a 9783036550138
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| 100 |
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|a Stefano, Alessandro
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| 245 |
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|a Image Processing and Analysis for Preclinical and Clinical Applications
|h Elektronische Ressource
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| 260 |
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|a Basel
|b MDPI - Multidisciplinary Digital Publishing Institute
|c 2022
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| 300 |
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|a 1 electronic resource (228 p.)
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| 653 |
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|a soft tissue sarcoma
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| 653 |
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|a zebrafish image analysis
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|a pulmonary vein ablation
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|a in vivo assay
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|a radiomics
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| 653 |
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|a neoadjuvant chemoradiation therapy (nCRT)
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| 653 |
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|a radiomics feature robustness
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|a magnetic resonance imaging (MRI)
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| 653 |
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|a computed tomography images
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|a maxillofacial fractures
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|a X-ray pre-processing
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|a colon
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|a imaging quantification
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|a image-patch voting
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|a stasis
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|a radiography
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|a n/a
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|a skin lesion
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|a MRI
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|a deep learning
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|a positron emission tomography-computed tomography
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| 653 |
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|a glomerular filtration rate
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|a Basal Cell Carcinoma
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|a PET/MRI co-registration
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|a xenotransplant
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|a ERFNet
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|a fundus image
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|a image registration
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|a volume estimation
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|a automated prostate-volume estimation
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|a renal depth
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|a 4D-flow
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|a image pre-processing
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|a gamma knife
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|a feature extraction
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|a computer-aided diagnosis
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|a transfer learning
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|a cancer cells
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|a Research & information: general / bicssc
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|a pathologic complete response (pCR)
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|a [11C]-methionine positron emission tomography
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|a rectal cancer
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|a cancer
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|a segmentation
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|a UNet
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|a Gate's method
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|a pipelined architecture
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|a abdominal ultrasound images
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|a artificial intelligence
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|a nuclear medicine
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|a classification
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|a high-level synthesis
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|a computed tomography
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|a convolutional neural network (CNN)
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|a convolutional neural network
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|a ENet
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|a medical-image analysis
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|a Chemistry / bicssc
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|a prostate
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| 653 |
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|a atrial fibrillation
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| 700 |
1 |
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|a Comelli, Albert
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| 700 |
1 |
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|a Vernuccio, Federica
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| 700 |
1 |
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|a Stefano, Alessandro
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b DOAB
|a Directory of Open Access Books
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| 500 |
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|a Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
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| 024 |
8 |
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|a 10.3390/books978-3-0365-5014-5
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| 856 |
4 |
2 |
|u https://directory.doabooks.org/handle/20.500.12854/97458
|z DOAB: description of the publication
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| 856 |
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|u https://www.mdpi.com/books/pdfview/book/5993
|7 0
|x Verlag
|3 Volltext
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|a Radiomics is one of the most successful branches of research in the field of image processing and analysis, as it provides valuable quantitative information for the personalized medicine. It has the potential to discover features of the disease that cannot be appreciated with the naked eye in both preclinical and clinical studies. In general, all quantitative approaches based on biomedical images, such as positron emission tomography (PET), computed tomography (CT) and magnetic resonance imaging (MRI), have a positive clinical impact in the detection of biological processes and diseases as well as in predicting response to treatment. This Special Issue, "Image Processing and Analysis for Preclinical and Clinical Applications", addresses some gaps in this field to improve the quality of research in the clinical and preclinical environment. It consists of fourteen peer-reviewed papers covering a range of topics and applications related to biomedical image processing and analysis.
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