AIMC Topic: Breast

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Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans.

Scientific reports
This paper performs a comprehensive study on the deep-learning-based computer-aided diagnosis (CADx) for the differential diagnosis of benign and malignant nodules/lesions by avoiding the potential errors caused by inaccurate image processing results...

Accelerated partial breast irradiation using robotic radiotherapy: a dosimetric comparison with tomotherapy and three-dimensional conformal radiotherapy.

Radiation oncology (London, England)
BACKGROUND: Accelerated partial breast irradiation (APBI) is a new breast treatment modality aiming to reduce treatment time using hypo fractionation. Compared to conventional whole breast irradiation that takes 5 to 6 weeks, APBI is reported to indu...

Unsupervised Deep Learning Applied to Breast Density Segmentation and Mammographic Risk Scoring.

IEEE transactions on medical imaging
Mammographic risk scoring has commonly been automated by extracting a set of handcrafted features from mammograms, and relating the responses directly or indirectly to breast cancer risk. We present a method that learns a feature hierarchy from unlab...

Monitoring vascular normalization induced by antiangiogenic treatment with (18)F-fluoromisonidazole-PET.

Molecular oncology
BACKGROUND: Rationalization of antiangiogenics requires biomarkers. Vascular re-normalization is one widely accepted mechanism of action for this drug class. The interstitium of tumors with abnormal vasculature is hypoxic. We sought to track vascular...

Is breast asymmetry caused by volume differences in women with pectus excavatum?

Journal of plastic, reconstructive & aesthetic surgery : JPRAS
This study determined the breast volumes of female patients with pectus excavatum that led to asymmetry and hypoplasia compared with normal women. This retrospective study enrolled 13 patients diagnosed with pectus excavatum and 13 normal women, rand...

Performance of a Knowledge-Based Model for Optimization of Volumetric Modulated Arc Therapy Plans for Single and Bilateral Breast Irradiation.

PloS one
PURPOSE: To evaluate the performance of a model-based optimisation process for volumetric modulated arc therapy, VMAT, applied to whole breast irradiation.

An Automatic Learning-Based Framework for Robust Nucleus Segmentation.

IEEE transactions on medical imaging
Computer-aided image analysis of histopathology specimens could potentially provide support for early detection and improved characterization of diseases such as brain tumor, pancreatic neuroendocrine tumor (NET), and breast cancer. Automated nucleus...

Fusing Heterogeneous Features From Stacked Sparse Autoencoder for Histopathological Image Analysis.

IEEE journal of biomedical and health informatics
In the analysis of histopathological images, both holistic (e.g., architecture features) and local appearance features demonstrate excellent performance, while their accuracy may vary dramatically when providing different inputs. This motivates us to...

Dynamic modeling of breast tissue with application of model reference adaptive system identification technique based on clinical robot-assisted palpation.

Journal of the mechanical behavior of biomedical materials
Accurate identification of breast tissue's dynamic behavior in physical examination is critical to successful diagnosis and treatment. In this study a model reference adaptive system identification (MRAS) algorithm is utilized to estimate the dynamic...