Artificial intelligence in ultrasound
YT Shen, L Chen, WW Yue, HX Xu - European Journal of Radiology, 2021 - Elsevier
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Ultrasonography of superficial soft-tissue masses: society of radiologists in ultrasound consensus conference statement
JA Jacobson, WD Middleton, SJ Allison, N Dahiya… - Radiology, 2022 - pubs.rsna.org
The Society of Radiologists in Ultrasound convened a panel of specialists from radiology,
orthopedic surgery, and pathology to arrive at a consensus regarding the management of …
orthopedic surgery, and pathology to arrive at a consensus regarding the management of …
Breast cancer classification from ultrasound images using probability-based optimal deep learning feature fusion
After lung cancer, breast cancer is the second leading cause of death in women. If breast
cancer is detected early, mortality rates in women can be reduced. Because manual breast …
cancer is detected early, mortality rates in women can be reduced. Because manual breast …
Breast Cancer Classification Depends on the Dynamic Dipper Throated Optimization Algorithm
According to the American Cancer Society, breast cancer is the second largest cause of
mortality among women after lung cancer. Women's death rates can be decreased if breast …
mortality among women after lung cancer. Women's death rates can be decreased if breast …
Prediction of Cognitive decline in Parkinson's Disease using clinical and DAT SPECT Imaging features, and Hybrid Machine Learning systems
M Hosseinzadeh, A Gorji, A Fathi Jouzdani… - Diagnostics, 2023 - mdpi.com
Background: We aimed to predict Montreal Cognitive Assessment (MoCA) scores in
Parkinson's disease patients at year 4 using handcrafted radiomics (RF), deep (DF), and …
Parkinson's disease patients at year 4 using handcrafted radiomics (RF), deep (DF), and …
Convolutional Neural Networks based classification of breast ultrasonography images by hybrid method with respect to benign, malignant, and normal using mRMR
Early diagnosis of breast lesions and differentiation of malignant lesions from benign lesions
are important for the prognosis of breast cancer. In the diagnosis of this disease ultrasound …
are important for the prognosis of breast cancer. In the diagnosis of this disease ultrasound …
Intratumoral and peritumoral radiomics based on functional parametric maps from breast DCE‐MRI for prediction of HER‐2 and Ki‐67 status
C Li, L Song, J Yin - Journal of Magnetic Resonance Imaging, 2021 - Wiley Online Library
Background Radiomics has been applied to breast magnetic resonance imaging (MRI) for
gene status prediction. However, the features of peritumoral regions were not thoroughly …
gene status prediction. However, the features of peritumoral regions were not thoroughly …
Deep learning for prediction of N2 metastasis and survival for clinical stage I non–small cell lung cancer
Background Preoperative mediastinal staging is crucial for the optimal management of
clinical stage I non–small cell lung cancer (NSCLC). Purpose To develop a deep learning …
clinical stage I non–small cell lung cancer (NSCLC). Purpose To develop a deep learning …
Boosted efficientnet: Detection of lymph node metastases in breast cancer using convolutional neural networks
Simple Summary The assistance of computer image analysis that automatically identifies
tissue or cell types has greatly improved histopathologic interpretation and diagnosis …
tissue or cell types has greatly improved histopathologic interpretation and diagnosis …
Assessment of intratumoral and peritumoral computed tomography radiomics for predicting pathological complete response to neoadjuvant chemoradiation in patients …
Importance For patients with locally advanced esophageal squamous cell carcinoma,
neoadjuvant chemoradiation has been shown to improve long-term outcomes, but the …
neoadjuvant chemoradiation has been shown to improve long-term outcomes, but the …