Texture Analysis of Ultrasound Images to Differentiate Simple Fibroadenomas From Complex Fibroadenomas and Benign Phyllodes Tumors.
Isil Basara AkinHakan Abdullah ÖzgülKursat SimsekCanan AltayMustafa SecilPinar BalciPublished in: Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine (2020)
As grayscale US features show prominent intersections, and treatment options differ, correct diagnosis is essential in SFAs, CFAs, and BPTs. In this study, we concluded that texture analysis of US images can discriminate SFAs from CFAs and BPTs. Texture analyses of US images is a potential candidate diagnostic tool for these lesions, and accurate diagnoses will preclude patients from undergoing unnecessary biopsies.
Keyphrases
- deep learning
- convolutional neural network
- end stage renal disease
- optical coherence tomography
- contrast enhanced
- newly diagnosed
- chronic kidney disease
- ejection fraction
- magnetic resonance imaging
- prognostic factors
- peritoneal dialysis
- high resolution
- ultrasound guided
- computed tomography
- magnetic resonance
- machine learning
- climate change
- risk assessment
- human health
- mass spectrometry
- patient reported