“Modern deep learning-based approaches have supplanted traditional approaches in image captioning, leading to more efficient and sophisticated models.” ScienceDirect.com
The field is shifting toward Multimodal Large Language Models (MLLMs) to provide better reasoning and generative flexibility. Community Perspectives
The extraction of visual information using models like CNNs or Vision Transformers. 126287
There is a critical need to bridge the "visual-pathological gap," as many standard models lack the ability to accurately describe pathological locations.
Traditional training data can lead to hallucinations or biased outputs, particularly in socio-economically diverse content. Traditional training data can lead to hallucinations or
Using attention mechanisms to identify the most relevant parts of an image for a specific description.
A significant portion of the review and subsequent research citing it (like work on uterine ultrasound captioning ) focuses on "computer-aided diagnosis". Key insights include: Key insights include: Translating those visual features into
Translating those visual features into coherent text using architectures like RNNs, LSTMs, and Transformers. 🏥 Focus on Medical Report Generation