National Institutes of Health (NIH)

Artificial intelligence (AI) tools have great potential in the field of biomedicine, particularly in the process of segmentation or annotating the pixels of an important structure in a medical image. Segmentation is critical for the identification of possible diseases or anomalies in body organs or cells. However, the challenge lies in the variability of the…

Segmentation, a practice in biomedicine whereby pixels from a significant structure in a medical image are annotated, can be aided by artificial intelligence (AI) models. However, these models often give only one solution, while the problem of medical image segmentation usually requires a range of interpretations. For instance, multiple human experts may have different perspectives…

In the realm of biomedicine, segmentation is a process where certain areas or pixels within a medical image, such as an organ or cell, are annotated or highlighted. This primarily assists clinicians in pinpointing areas showing signs of diseases or abnormalities. However, there is often a gray area since different experts can have differing interpretations…

Biomedical segmentation pertains to marking pixels from significant structures in a medical image like cells or organs which is crucial for disease diagnosis and treatment. Generally, a single answer is provided by most artificial intelligence (AI) models while making these annotations, but such a process is not always straightforward. In a recent paper, Marianne Rakic, an…

A research team from MIT, the Broad Institute of MIT and Harvard, and Massachusetts General Hospital has developed an artificial intelligence (AI) tool, named Tyche, that presents multiple plausible interpretations of medical images, highlighting potentially important and varied insights. This tool aims to address the often complex ambiguity in medical image interpretation where different experts…

Medical imaging is a critical tool in diagnosing and monitoring disease. However, interpreting these images is not always straightforward, leading to potential disagreement amongst clinicians. To address this issue, researchers at MIT, in collaboration with the Broad Institute of MIT and Harvard, and Massachusetts General Hospital (MGH), have developed an artificial intelligence (AI) tool, named…

In biomedical science, the process of annotating pixels from crucial elements within a medical image, such as a cell or organ, is called segmentation. This task can be aided by artificial intelligence (AI), which highlights pixels that might indicate the existence of a certain disease or anomaly. However, segmentation is seldom clear-cut, as a group…

Artificial Intelligence (AI) models are increasingly being employed in the field of biomedicine to assist clinicians with image segmentation, a process that annotates pixels from important structures in a medical image, such as an organ or cell. However, these AI models often offer a singular answer, while image segmentation in the medical field is usually…

In the field of biomedicine, segmentation plays a crucial role in identifying and highlighting essential structures in medical images, such as organs or cells. In recent times, artificial intelligence (AI) models have shown promise in aiding clinicians by identifying pixels that may indicate disease or anomalies. However, there is a consensus that this method is…

In biomedicine, the process of segmentation involves marking significant structures in a medical image, such as cells or organs. This can aid in the detection and treatment of diseases visible in these images. Despite this promise, current artificial intelligence (AI) systems used for medical image segmentation only offer a single segmentation result. This approach isn't…