Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives
Transformer, one of the latest technological advances of deep learning, has gained
prevalence in natural language processing or computer vision. Since medical imaging bear …
prevalence in natural language processing or computer vision. Since medical imaging bear …
A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises
SK Zhou, H Greenspan, C Davatzikos… - Proceedings of the …, 2021 - ieeexplore.ieee.org
Since its renaissance, deep learning has been widely used in various medical imaging tasks
and has achieved remarkable success in many medical imaging applications, thereby …
and has achieved remarkable success in many medical imaging applications, thereby …
Artificial intelligence and machine learning for medical imaging: A technology review
Artificial intelligence (AI) has recently become a very popular buzzword, as a consequence
of disruptive technical advances and impressive experimental results, notably in the field of …
of disruptive technical advances and impressive experimental results, notably in the field of …
[HTML][HTML] A machine learning approach to diagnosing lung and colon cancer using a deep learning-based classification framework
The field of Medicine and Healthcare has attained revolutionary advancements in the last
forty years. Within this period, the actual reasons behind numerous diseases were unveiled …
forty years. Within this period, the actual reasons behind numerous diseases were unveiled …
[HTML][HTML] Knowledge matters: Chest radiology report generation with general and specific knowledge
Automatic chest radiology report generation is critical in clinics which can relieve
experienced radiologists from the heavy workload and remind inexperienced radiologists of …
experienced radiologists from the heavy workload and remind inexperienced radiologists of …
[HTML][HTML] Transfer learning in magnetic resonance brain imaging: A systematic review
(1) Background: Transfer learning refers to machine learning techniques that focus on
acquiring knowledge from related tasks to improve generalization in the tasks of interest. In …
acquiring knowledge from related tasks to improve generalization in the tasks of interest. In …
State-of-the-art review of machine learning applications in additive manufacturing; from design to manufacturing and property control
In this review, some of the latest applicable methods of machine learning (ML) in additive
manufacturing (AM) have been presented and the classification of the most common ML …
manufacturing (AM) have been presented and the classification of the most common ML …
[HTML][HTML] Dementia detection from speech using machine learning and deep learning architectures
Dementia affects the patient's memory and leads to language impairment. Research has
demonstrated that speech and language deterioration is often a clear indication of dementia …
demonstrated that speech and language deterioration is often a clear indication of dementia …
Brain tumor classification based on hybrid optimized multi-features analysis using magnetic resonance imaging dataset
Brain tumors are deadly but become deadliest because of delayed and inefficient diagnosis
process. Large variations in tumor types also instigate additional complexity. Machine vision …
process. Large variations in tumor types also instigate additional complexity. Machine vision …
LE-UDA: Label-efficient unsupervised domain adaptation for medical image segmentation
While deep learning methods hitherto have achieved considerable success in medical
image segmentation, they are still hampered by two limitations:(i) reliance on large-scale …
image segmentation, they are still hampered by two limitations:(i) reliance on large-scale …