Segment anything model for medical images?
Abstract The Segment Anything Model (SAM) is the first foundation model for general image
segmentation. It has achieved impressive results on various natural image segmentation …
segmentation. It has achieved impressive results on various natural image segmentation …
CT‐based automatic spine segmentation using patch‐based deep learning
CT vertebral segmentation plays an essential role in various clinical applications, such as
computer‐assisted surgical interventions, assessment of spinal abnormalities, and vertebral …
computer‐assisted surgical interventions, assessment of spinal abnormalities, and vertebral …
VerSe: a vertebrae labelling and segmentation benchmark for multi-detector CT images
Vertebral labelling and segmentation are two fundamental tasks in an automated spine
processing pipeline. Reliable and accurate processing of spine images is expected to …
processing pipeline. Reliable and accurate processing of spine images is expected to …
Deep learning-based medical images segmentation of musculoskeletal anatomical structures: a survey of bottlenecks and strategies
L Bonaldi, A Pretto, C Pirri, F Uccheddu, CG Fontanella… - Bioengineering, 2023 - mdpi.com
By leveraging the recent development of artificial intelligence algorithms, several medical
sectors have benefited from using automatic segmentation tools from bioimaging to segment …
sectors have benefited from using automatic segmentation tools from bioimaging to segment …
A review of CT-based fracture risk assessment with finite element modeling and machine learning
Abstract Purpose of Review We reviewed advances over the past 3 years in assessment of
fracture risk based on CT scans, considering methods that use finite element models …
fracture risk based on CT scans, considering methods that use finite element models …
Stu-net: Scalable and transferable medical image segmentation models empowered by large-scale supervised pre-training
Large-scale models pre-trained on large-scale datasets have profoundly advanced the
development of deep learning. However, the state-of-the-art models for medical image …
development of deep learning. However, the state-of-the-art models for medical image …
MedShapeNet--A large-scale dataset of 3D medical shapes for computer vision
We present MedShapeNet, a large collection of anatomical shapes (eg, bones, organs,
vessels) and 3D surgical instrument models. Prior to the deep learning era, the broad …
vessels) and 3D surgical instrument models. Prior to the deep learning era, the broad …
Segvol: Universal and interactive volumetric medical image segmentation
Precise image segmentation provides clinical study with meaningful and well-structured
information. Despite the remarkable progress achieved in medical image segmentation …
information. Despite the remarkable progress achieved in medical image segmentation …
The RSNA cervical spine fracture CT dataset
HM Lin, E Colak, T Richards, FC Kitamura… - Radiology: Artificial …, 2023 - pubs.rsna.org
The RSNA Cervical Spine Fracture CT Dataset Page 1 Page 1 of 21 The RSNA Cervical Spine
Fracture CT Dataset Hui Ming Lin, HBSc Errol Colak, MD Tyler Richards, MD Felipe C. Kitamura …
Fracture CT Dataset Hui Ming Lin, HBSc Errol Colak, MD Tyler Richards, MD Felipe C. Kitamura …
Detailed annotations of chest x-rays via ct projection for report understanding
In clinical radiology reports, doctors capture important information about the patient's health
status. They convey their observations from raw medical imaging data about the inner …
status. They convey their observations from raw medical imaging data about the inner …