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Towards generalizable tumor synthesis
Tumor synthesis enables the creation of artificial tumors in medical images facilitating the
training of AI models for tumor detection and segmentation. However success in tumor …
training of AI models for tumor detection and segmentation. However success in tumor …
Abdomenatlas: A large-scale, detailed-annotated, & multi-center dataset for efficient transfer learning and open algorithmic benchmarking
We introduce the largest abdominal CT dataset (termed AbdomenAtlas) of 20,460 three-
dimensional CT volumes sourced from 112 hospitals across diverse populations …
dimensional CT volumes sourced from 112 hospitals across diverse populations …
Abdomenatlas-8k: Annotating 8,000 ct volumes for multi-organ segmentation in three weeks
Annotating medical images, particularly for organ segmentation, is laborious and time-
consuming. For example, annotating an abdominal organ requires an estimated rate of 30 …
consuming. For example, annotating an abdominal organ requires an estimated rate of 30 …
Universal and extensible language-vision models for organ segmentation and tumor detection from abdominal computed tomography
The advancement of artificial intelligence (AI) for organ segmentation and tumor detection is
propelled by the growing availability of computed tomography (CT) datasets with detailed …
propelled by the growing availability of computed tomography (CT) datasets with detailed …
[HTML][HTML] Medshapenet–a large-scale dataset of 3d medical shapes for computer vision
Objectives The shape is commonly used to describe the objects. State-of-the-art algorithms
in medical imaging are predominantly diverging from computer vision, where voxel grids …
in medical imaging are predominantly diverging from computer vision, where voxel grids …
Touchstone benchmark: Are we on the right way for evaluating AI algorithms for medical segmentation?
How can we test AI performance? This question seems trivial, but it isn't. Standard
benchmarks often have problems such as in-distribution and small-size test sets …
benchmarks often have problems such as in-distribution and small-size test sets …
From pixel to cancer: Cellular automata in computed tomography
AI for cancer detection encounters the bottleneck of data scarcity, annotation difficulty, and
low prevalence of early tumors. Tumor synthesis seeks to create artificial tumors in medical …
low prevalence of early tumors. Tumor synthesis seeks to create artificial tumors in medical …
Exploiting structural consistency of chest anatomy for unsupervised anomaly detection in radiography images
Radiography imaging protocols focus on particular body regions, therefore producing
images of great similarity and yielding recurrent anatomical structures across patients …
images of great similarity and yielding recurrent anatomical structures across patients …
Boosting dermatoscopic lesion segmentation via diffusion models with visual and textual prompts
Image synthesis approaches, eg, generative adversarial networks, have been popular as a
form of data augmentation in medical image analysis tasks. It is primarily beneficial to …
form of data augmentation in medical image analysis tasks. It is primarily beneficial to …
Acquiring weak annotations for tumor localization in temporal and volumetric data
Creating large-scale and well-annotated datasets to train AI algorithms is crucial for
automated tumor detection and localization. However, with limited resources, it is …
automated tumor detection and localization. However, with limited resources, it is …