Radiomics in Breast Imaging: Future Development.
Alessandra PanicoGianluca GattaAntonio SalviaGraziella Di GreziaNoemi FicoVincenzo CuccurulloPublished in: Journal of personalized medicine (2023)
Breast cancer is the most common and most commonly diagnosed non-skin cancer in women. There are several risk factors related to habits and heredity, and screening is essential to reduce the incidence of mortality. Thanks to screening and increased awareness among women, most breast cancers are diagnosed at an early stage, increasing the chances of cure and survival. Regular screening is essential. Mammography is currently the gold standard for breast cancer diagnosis. In mammography, we can encounter problems with the sensitivity of the instrument; in fact, in the case of a high density of glands, the ability to detect small masses is reduced. In fact, in some cases, the lesion may not be particularly evident, it may be hidden, and it is possible to incur false negatives as partial details that may escape the radiologist's eye. The problem is, therefore, substantial, and it makes sense to look for techniques that can increase the quality of diagnosis. In recent years, innovative techniques based on artificial intelligence have been used in this regard, which are able to see where the human eye cannot reach. In this paper, we can see the application of radiomics in mammography.
Keyphrases
- contrast enhanced
- artificial intelligence
- risk factors
- high density
- early stage
- magnetic resonance imaging
- polycystic ovary syndrome
- machine learning
- skin cancer
- magnetic resonance
- big data
- deep learning
- computed tomography
- breast cancer risk
- high resolution
- endothelial cells
- lymph node metastasis
- image quality
- type diabetes
- current status
- young adults
- insulin resistance
- radiation therapy
- squamous cell carcinoma
- coronary artery disease
- adipose tissue
- childhood cancer
- mass spectrometry