Advanced Computational Methods for Oncological Image Analysis

Advanced Computational Methods for Oncological Image Analysis

[Cancer is the second most common cause of death worldwide and encompasses highly variable clinical and biological scenarios. Some of the current clinical challenges are (i) early diagnosis of the disease and (ii) precision medicine, which allows for treatments targeted to specific clinical cases. T...

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محفوظ في:
التفاصيل البيبلوغرافية
مؤلفون آخرون: Rundo, Leonardo (المحرر), Militello, Carmelo (المحرر), Conti, Vincenzo (المحرر), Zaccagna, Fulvio (المحرر), Han, Changhee (المحرر)
التنسيق: فصل الكتاب
منشور في: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
الموضوعات:
Medicine
melanoma detection
deep learning
transfer learning
ensemble classification
3D-CNN
immunotherapy
radiomics
self-attention
breast imaging
microwave imaging
image reconstruction
segmentation
unsupervised machine learning
k-means clustering
Kolmogorov-Smirnov hypothesis test
statistical inference
performance metrics
contrast source inversion
brain tumor segmentation
magnetic resonance imaging
survey
brain MRI image
tumor region
skull stripping
region growing
U-Net
BRATS dataset
incoherent imaging
clutter rejection
breast cancer detection
MRgFUS
proton resonance frequency shift
temperature variations
referenceless thermometry
RBF neural networks
interferometric optical fibers
breast cancer
risk assessment
machine learning
texture
mammography
medical imaging
imaging biomarkers
bone scintigraphy
prostate cancer
semisupervised classification
false positives reduction
computer-aided detection
breast mass
mass detection
mass segmentation
Mask R-CNN
dataset partition
brain tumor
classification
shallow machine learning
breast cancer diagnosis
Wisconsin Breast Cancer Dataset
feature selection
dimensionality reduction
principal component analysis
ensemble method
n/a
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DOAB: description of the publication
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