AIMC Topic: Female

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Improving Image Quality and Reducing Scan Time for Synthetic MRI of Breast by Using Deep Learning Reconstruction.

BioMed research international
OBJECTIVES: To investigate a deep learning reconstruction algorithm to reduce the time of synthetic MRI (SynMRI) scanning on the breast and improve the image quality.

Utility of Fully Automated Body Composition Measures on Pretreatment Abdominal CT for Predicting Survival in Patients With Colorectal Cancer.

AJR. American journal of roentgenology
CT examinations contain opportunistic body composition data with potential prognostic utility. Previous studies have primarily used manual or semiautomated tools to evaluate body composition in patients with colorectal cancer (CRC). The purpose of ...

Artificial intelligence computer-aided detection enhances synthesized mammograms: comparison with original digital mammograms alone and in combination with tomosynthesis images in an experimental setting.

Breast cancer (Tokyo, Japan)
BACKGROUND: It remains unclear whether original full-field digital mammograms (DMs) can be replaced with synthesized mammograms in both screening and diagnostic settings. To compare reader performance of artificial intelligence computer-aided detecti...

Comparisons of deep learning and machine learning while using text mining methods to identify suicide attempts of patients with mood disorders.

Journal of affective disorders
BACKGROUND: Suicide attempt is one of the most severe consequences for patients with mood disorders. This study aimed to perform deep learning and machine learning while using text mining to identify patients with suicide attempts and to compare thei...

Domain generalization in deep learning based mass detection in mammography: A large-scale multi-center study.

Artificial intelligence in medicine
Computer-aided detection systems based on deep learning have shown great potential in breast cancer detection. However, the lack of domain generalization of artificial neural networks is an important obstacle to their deployment in changing clinical ...

C-Net: Cascaded convolutional neural network with global guidance and refinement residuals for breast ultrasound images segmentation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Breast lesions segmentation is an important step of computer-aided diagnosis system. However, speckle noise, heterogeneous structure, and similar intensity distributions bring challenges for breast lesion segmentation.

Dual-Scale Doppler Attention for Human Identification.

Sensors (Basel, Switzerland)
This paper considers a Deep Convolutional Neural Network (DCNN) with an attention mechanism referred to as Dual-Scale Doppler Attention (DSDA) for human identification given a micro-Doppler (MD) signature induced as input. The MD signature includes u...

Antenna Excitation Optimization with Deep Learning for Microwave Breast Cancer Hyperthermia.

Sensors (Basel, Switzerland)
Microwave hyperthermia (MH) requires the effective calibration of antenna excitations for the selective focusing of the microwave energy on the target region, with a nominal effect on the surrounding tissue. To this end, many different antenna calibr...

The potential of predictive and prognostic breast MRI (P2-bMRI).

European radiology experimental
Magnetic resonance imaging (MRI) is an important part of breast cancer diagnosis and multimodal workup. It provides unsurpassed soft tissue contrast to analyse the underlying pathophysiology, and it is adopted for a variety of clinical indications. P...