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Image Processing and Analysis for Preclinical and Clinical Applications

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 p...

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Salvato in:
Natura: Online
Lingua:inglese
Pubblicazione: MDPI - Multidisciplinary Digital Publishing Institute 2023
Soggetti:
deep learning
segmentation
prostate
MRI
ENet
UNet
ERFNet
radiomics
gamma knife
imaging quantification
[11C]-methionine positron emission tomography
cancer
atrial fibrillation
4D-flow
stasis
pulmonary vein ablation
convolutional neural network
transfer learning
maxillofacial fractures
computed tomography images
radiography
xenotransplant
cancer cells
zebrafish image analysis
in vivo assay
convolutional neural network (CNN)
magnetic resonance imaging (MRI)
neoadjuvant chemoradiation therapy (nCRT)
pathologic complete response (pCR)
rectal cancer
radiomics feature robustness
PET/MRI co-registration
image registration
fundus image
feature extraction
glomerular filtration rate
Gate’s method
renal depth
computed tomography
computer-aided diagnosis
medical-image analysis
automated prostate-volume estimation
abdominal ultrasound images
image-patch voting
soft tissue sarcoma
volume estimation
artificial intelligence
Basal Cell Carcinoma
skin lesion
classification
colon
positron emission tomography-computed tomography
nuclear medicine
image pre-processing
high-level synthesis
X-ray pre-processing
pipelined architecture
n/a
thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
thema EDItEUR::P Mathematics and Science::PN Chemistry
Accesso online:ONIX_20230220_9783036550138_61
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Riassunto: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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