Advances in medical image analysis with vision transformers: a comprehensive review

R Azad, A Kazerouni, M Heidari, EK Aghdam… - Medical Image …, 2024 - Elsevier
The remarkable performance of the Transformer architecture in natural language processing
has recently also triggered broad interest in Computer Vision. Among other merits …

Diffusion models in medical imaging: A comprehensive survey

A Kazerouni, EK Aghdam, M Heidari, R Azad… - Medical Image …, 2023 - Elsevier
Denoising diffusion models, a class of generative models, have garnered immense interest
lately in various deep-learning problems. A diffusion probabilistic model defines a forward …

Machine learning and deep learning methods for skin lesion classification and diagnosis: a systematic review

MA Kassem, KM Hosny, R Damaševičius, MM Eltoukhy - Diagnostics, 2021 - mdpi.com
Computer-aided systems for skin lesion diagnosis is a growing area of research. Recently,
researchers have shown an increasing interest in develo** computer-aided diagnosis …

Is it time to replace cnns with transformers for medical images?

C Matsoukas, JF Haslum, M Söderberg… - arxiv preprint arxiv …, 2021 - arxiv.org
Convolutional Neural Networks (CNNs) have reigned for a decade as the de facto approach
to automated medical image diagnosis. Recently, vision transformers (ViTs) have appeared …

Dynamically weighted balanced loss: class imbalanced learning and confidence calibration of deep neural networks

KRM Fernando, CP Tsokos - IEEE Transactions on Neural …, 2021 - ieeexplore.ieee.org
Imbalanced class distribution is an inherent problem in many real-world classification tasks
where the minority class is the class of interest. Many conventional statistical and machine …