A review of convolutional neural network architectures and their optimizations
The research advances concerning the typical architectures of convolutional neural
networks (CNNs) as well as their optimizations are analyzed and elaborated in detail in this …
networks (CNNs) as well as their optimizations are analyzed and elaborated in detail in this …
Bidirectional copy-paste for semi-supervised medical image segmentation
In semi-supervised medical image segmentation, there exist empirical mismatch problems
between labeled and unlabeled data distribution. The knowledge learned from the labeled …
between labeled and unlabeled data distribution. The knowledge learned from the labeled …
[HTML][HTML] Artificial Intelligence in Pancreatic Image Analysis: A Review
Pancreatic cancer is a highly lethal disease with a poor prognosis. Its early diagnosis and
accurate treatment mainly rely on medical imaging, so accurate medical image analysis is …
accurate treatment mainly rely on medical imaging, so accurate medical image analysis is …
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 …
Devil is in the queries: advancing mask transformers for real-world medical image segmentation and out-of-distribution localization
Real-world medical image segmentation has tremendous long-tailed complexity of objects,
among which tail conditions correlate with relatively rare diseases and are clinically …
among which tail conditions correlate with relatively rare diseases and are clinically …
Squid: Deep feature in-painting for unsupervised anomaly detection
Radiography imaging protocols focus on particular body regions, therefore producing
images of great similarity and yielding recurrent anatomical structures across patients. To …
images of great similarity and yielding recurrent anatomical structures across patients. To …
Zept: Zero-shot pan-tumor segmentation via query-disentangling and self-prompting
The long-tailed distribution problem in medical image analysis reflects a high prevalence of
common conditions and a low prevalence of rare ones which poses a significant challenge …
common conditions and a low prevalence of rare ones which poses a significant challenge …
DeepPrognosis: Preoperative prediction of pancreatic cancer survival and surgical margin via comprehensive understanding of dynamic contrast-enhanced CT …
Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers and carries a
dismal prognosis of∼ 10% in five year survival rate. Surgery remains the best option of a …
dismal prognosis of∼ 10% in five year survival rate. Surgery remains the best option of a …
Effective pancreatic cancer screening on non-contrast CT scans via anatomy-aware transformers
Pancreatic cancer is a relatively uncommon but most deadly cancer. Screening the general
asymptomatic population is not recommended due to the risk that a significant number of …
asymptomatic population is not recommended due to the risk that a significant number of …
The felix project: Deep networks to detect pancreatic neoplasms
Tens of millions of abdominal images are performed with computed tomography (CT) in the
US each year but pancreatic cancers are sometimes not initially detected in these images …
US each year but pancreatic cancers are sometimes not initially detected in these images …