concept

medical image report generation

Also known as: medical image report generation, Imaging Report Generation, Image-Report Generation

Facts (11)

Sources

Detecting and Evaluating Medical Hallucinations in Large Vision ... arxiv.org arXiv Jun 14, 2024 11 facts

claimThe hallucination detection instruction pair data used for training MediHallDetector is divided into two parts: instructions for detecting hallucinations in Visual Question Answering (VQA) tasks and instructions for detecting hallucinations in Image Report Generation (IRG) tasks.

claimThe medical image report generation (IRG) task is classified as a type of image depiction question.

procedureIn coarse-grained multi-dimension Image-Report Generation (IRG) scenarios, Large Vision-Language Model (LVLM) outputs are segmented into sentences and annotated at the sentence level.

claimLarge Vision Language Models (LVLMs) are increasingly used in healthcare applications, such as medical visual question answering and imaging report generation.

claimIn Image-Report Generation (IRG) tasks, mere correctness does not capture an LVLM's judgment of factuality across all dimensions when the model needs to analyze image content from various dimensions.

procedureIn the Image Report Generation (IRG) scenario for Med-HallMark, 1800 images and their corresponding medical reports were sampled from the MIMIC-test and OpenI datasets.

procedureTo guide models in performing medical image report generation (IRG) tasks, the authors employ five different manually designed instructions intended to ensure the model provides comprehensive descriptions of the medical images.

claimThe prompts used in Image Report Generation (IRG) tasks are sufficiently clear and detailed to eliminate prompt-induced hallucinations.

claimIn Image Report Generation (IRG) tasks, all images are chest X-rays, which prevents minor hallucinations from occurring.

claimIn Med-HallMark, Medical Visual Question Answering (Med-VQA) tasks consist of Question-Answer pairs that examine image understanding from a single fine-grained perspective, while Imaging Report Generation (IRG) tasks consist of instruction pairs that require the model to describe a medical image from a global perspective.

claimMed-HallMark supports two primary medical multimodal task types: Medical Visual Question Answering (Med-VQA) and Imaging Report Generation (IRG).