AIMC Topic: Pectoralis Muscles

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Impact of pectoral muscle removal on deep-learning-based breast cancer risk prediction.

Physics in medicine and biology
State-of-the-art breast cancer risk (BCR) prediction models have been originally trained on mammograms with pectoral muscle (PM) included. This study investigated whether excluding PM during training/fine-tuning improves the model's BCR discriminatio...

Proteomics and machine learning in the prediction and explanation of low pectoralis muscle area.

Scientific reports
Low muscle mass is associated with numerous adverse outcomes independent of other associated comorbid diseases. We aimed to predict and understand an individual's risk for developing low muscle mass using proteomics and machine learning. We identifie...

CT-derived pectoralis composition and incident pneumonia hospitalization using fully automated deep-learning algorithm: multi-ethnic study of atherosclerosis.

European radiology
BACKGROUND: Pneumonia-related hospitalization may be associated with advanced skeletal muscle loss due to aging (i.e., sarcopenia) or chronic illnesses (i.e., cachexia). Early detection of muscle loss may now be feasible using deep-learning algorithm...

Deep learning-based pectoralis muscle volume segmentation method from chest computed tomography image using sagittal range detection and axial slice-based segmentation.

PloS one
The pectoralis muscle is an important indicator of respiratory muscle function and has been linked to various parenchymal biomarkers, such as airflow limitation severity and diffusing capacity for carbon monoxide, which are widely used in diagnosing ...

Pectoralis muscle predicts distant metastases in breast cancer by deep learning radiomics.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Sarcopenia is associated with a poor prognosis in patients with breast cancer (BC). Currently, there are few quantitative assessments carried out between muscle biomarkers and distant metastasis using existing methods.

Uncertainty estimation for deep learning-based pectoral muscle segmentation via Monte Carlo dropout.

Physics in medicine and biology
. Deep Learning models are often susceptible to failures after deployment. Knowing when your model is producing inadequate predictions is crucial. In this work, we investigate the utility of Monte Carlo (MC) dropout and the efficacy of the proposed u...

A deep learning-based automated image analysis for histological evaluation of broiler pectoral muscle.

Poultry science
Global market demand for chicken breast muscle with high yield and quality, together with the high incidence rate of breast muscle abnormalities in recent years highlights the need for tools that can provide a rapid and precise evaluation of breast m...

Automatic MRI segmentation of pectoralis major muscle using deep learning.

Scientific reports
To develop and validate a deep convolutional neural network (CNN) method capable of selecting the greatest Pectoralis Major Cross-Sectional Area (PMM-CSA) and automatically segmenting PMM on an axial Magnetic Resonance Imaging (MRI). We hypothesized ...

Breast pectoral muscle segmentation in mammograms using a modified holistically-nested edge detection network.

Medical image analysis
This paper presents a method for automatic breast pectoral muscle segmentation in mediolateral oblique mammograms using a Convolutional Neural Network (CNN) inspired by the Holistically-nested Edge Detection (HED) network. Most of the existing method...