Abstract
In the world, breast cancer is the most commonly diagnosed cancer among women. Currently, MRI is the most sensitive breast imaging method for detecting breast cancer, although false positive rates are still an issue. To date, the accuracy of breast MRI is widely recognized across various clinical scenarios, in particular, staging of known cancer, screening for breast cancer in high-risk women, and evaluation of response to neoadjuvant chemotherapy. Since technical development and further clinical indications have expanded over recent years, dedicated breast radiologists need to constantly update their knowledge and expertise to remain confident and maintain high levels of diagnostic performance in breast MRI. This review aims to detail current and future applications of breast MRI, from technological requirements and advances to new multiparametric and abbreviated protocols, and ultrafast imaging, as well as current and future indications.
Keywords: Breast cancer, Magnetic resonance imaging, Diffusion, BI-RADS, Screening, Chemotherapy.
Call for Papers in Thematic Issues
Emerging Trends & Techniques in Medical Imaging using Machine Learning and Deep Learning Techniques
This special issue will aim to discuss different approaches, initiatives and applications in Medical Imaging fields (including Machine Intelligence, Mining Engineering, Modeling and Simulation, Computer, Communication, Networking and Information Engineering, Systems Engineering, Innovative Computing Systems, Adaptive Technologies for Sustainable Growth, and Theoretical and Applied Sciences). This collection should inspire various ...read more
Intelligent Information Retrieval for Multispectral and Hyperspectral Imaging
Multispectral and hyperspectral imaging is an interdisciplinary research area, widely focuses on spectral, spatial, and temporal data. It offers a plethora of opportunities to efficiently analyze the vast area of the earth's surface. However, there are numerous factors such as dimensionality and size of the hyperspectral data, lesser training samples, ...read more
Multimodal Imaging Using Spectroscopic Techniques for Improved Surgical Guidance
The majority of patients with solid malignancies have surgical excision as their primary and most successful method of medical care. On the other hand, patients experience recurrence and subsequent recurrence. Their objective was to provide a simpler and more concise explanation of the obstacles faced by physicians and the ways ...read more
Quantum Machine Learning for Medical Data and Imaging
Quantum computing has promised a significant speedup in certain computationally intensive tasks that are intractable on classical computers. Researchers in quantum machine learning, such as those working in computer vision, image processing, biomedical analysis, and related topics, may play an important role in comprehending and working on complicated medical data, ...read more
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