Search Results for author: Anand Shah

Found 7 papers, 2 papers with code

Zero-Shot ECG Classification with Multimodal Learning and Test-time Clinical Knowledge Enhancement

no code implementations11 Mar 2024 Che Liu, Zhongwei Wan, Cheng Ouyang, Anand Shah, Wenjia Bai, Rossella Arcucci

Through multimodal learning on ECG records and associated reports, MERL is capable of performing zero-shot ECG classification with text prompts, eliminating the need for training data in downstream tasks.

Clinical Knowledge Descriptive +5

G2D: From Global to Dense Radiography Representation Learning via Vision-Language Pre-training

no code implementations3 Dec 2023 Che Liu, Cheng Ouyang, Sibo Cheng, Anand Shah, Wenjia Bai, Rossella Arcucci

G2D achieves superior performance across 6 medical imaging tasks and 25 diseases, particularly in semantic segmentation, which necessitates fine-grained, semantically-grounded image features.

object-detection Object Detection +5

IMITATE: Clinical Prior Guided Hierarchical Vision-Language Pre-training

no code implementations11 Oct 2023 Che Liu, Sibo Cheng, Miaojing Shi, Anand Shah, Wenjia Bai, Rossella Arcucci

The framework derives multi-level visual features from the chest X-ray (CXR) images and separately aligns these features with the descriptive and the conclusive text encoded in the hierarchical medical report.

Contrastive Learning Descriptive

Utilizing Synthetic Data for Medical Vision-Language Pre-training: Bypassing the Need for Real Images

1 code implementation10 Oct 2023 Che Liu, Anand Shah, Wenjia Bai, Rossella Arcucci

The advent of text-guided generative models raises a compelling question: Can VLP be implemented solely with synthetic images generated from genuine radiology reports, thereby mitigating the need for extensively pairing and curating image-text datasets?

Image Classification object-detection +2

M-FLAG: Medical Vision-Language Pre-training with Frozen Language Models and Latent Space Geometry Optimization

1 code implementation17 Jul 2023 Che Liu, Sibo Cheng, Chen Chen, Mengyun Qiao, Weitong Zhang, Anand Shah, Wenjia Bai, Rossella Arcucci

The proposed method, named Medical vision-language pre-training with Frozen language models and Latent spAce Geometry optimization (M-FLAG), leverages a frozen language model for training stability and efficiency and introduces a novel orthogonality loss to harmonize the latent space geometry.

Image Classification Language Modelling +3

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