AI Medical Compendium Topic:
Radiographic Image Interpretation, Computer-Assisted

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Computer-aided Detection and Diagnosis of Cancer Regions in Mammogram Images Using Resource-Efficient CNN Architecture.

Current medical imaging
AIM: The automatic computer-assisted mammogram classification system is important for women patients to detect and diagnose the cancer regions. In this work, the mammogram images are classified into three cases: healthy, benign and cancer, using the ...

Precancerous Change Detection Technique on Mammography Breast Cancer Images based on Mean Ratio and Log Ratio using Fuzzy c Mean Classification with Gabor Filter.

Current medical imaging
BACKGROUND: The growing rate of breast cancer necessitates immediate global attention. Mammography images are used to determine the stage of malignancy. Breast cancer stages must be identified in order to save a person's life.

Breast Mass Detection and Classification Using Machine Learning Approaches on Two-Dimensional Mammogram: A Review.

Critical reviews in biomedical engineering
Breast cancer is a leading cause of mortality among women, both in India and globally. The prevalence of breast masses is notably common in women aged 20 to 60. These breast masses are classified, according to the breast imaging-reporting and data sy...

Peri-lesion regions in differentiating suspicious breast calcification-only lesions specifically on contrast enhanced mammography.

Journal of X-ray science and technology
PURPOSE: The explore the added value of peri-calcification regions on contrast-enhanced mammography (CEM) in the differential diagnosis of breast lesions presenting as only calcification on routine mammogram.

Deep-learning reconstruction for the evaluation of lumbar spinal stenosis in computed tomography.

Medicine
To compare the quality and interobserver agreement in the evaluation of lumbar spinal stenosis (LSS) on computed tomography (CT) images between deep-learning reconstruction (DLR) and hybrid iterative reconstruction (hybrid IR). This retrospective stu...

[Quality of Images Reconstructed by Deep Learning Reconstruction Algorithm for Head and Neck CT Angiography at 100 kVp].

Zhongguo yi xue ke xue yuan xue bao. Acta Academiae Medicinae Sinicae
Objective To evaluate the impact of deep learning reconstruction algorithm on the image quality of head and neck CT angiography (CTA) at 100 kVp. Methods CT scanning was performed at 100 kVp for the 37 patients who underwent head and neck CTA in PUMC...

Clinical Impact of Deep Learning Reconstruction in MRI.

Radiographics : a review publication of the Radiological Society of North America, Inc
Deep learning has been recognized as a paradigm-shifting tool in radiology. Deep learning reconstruction (DLR) has recently emerged as a technology used in the image reconstruction process of MRI, which is an essential procedure in generating MR imag...