Overview of the HECKTOR challenge at MICCAI 2021: automatic head and neck tumor segmentation and outcome prediction in PET/CT images
V Andrearczyk, V Oreiller, S Boughdad… - 3D head and neck tumor …, 2021 - Springer
This paper presents an overview of the second edition of the HEad and neCK TumOR
(HECKTOR) challenge, organized as a satellite event of the 24th International Conference …
(HECKTOR) challenge, organized as a satellite event of the 24th International Conference …
Narrative review on the role of imaging in DDH
S Ghasseminia, AR Hareendranathan… - Indian Journal of …, 2021 - Springer
Background Developmental dysplasia of hip (DDH) represents a spectrum from acetabular
dysplasia to fixed dislocation, giving disability through premature osteoarthritis. Most DDH …
dysplasia to fixed dislocation, giving disability through premature osteoarthritis. Most DDH …
3D bounding box detection in volumetric medical image data: A systematic literature review
D Kern, A Mastmeyer - 2021 IEEE 8th International Conference …, 2021 - ieeexplore.ieee.org
This paper discusses current methods and trends for 3D bounding box detection in
volumetric medical image data. For this purpose, an overview of relevant papers from recent …
volumetric medical image data. For this purpose, an overview of relevant papers from recent …
Attention by selection: A deep selective attention approach to breast cancer classification
Deep learning approaches are widely applied to histopathological image analysis due to the
impressive levels of performance achieved. However, when dealing with high-resolution …
impressive levels of performance achieved. However, when dealing with high-resolution …
3-D RoI-aware U-net for accurate and efficient colorectal tumor segmentation
Segmentation of colorectal cancerous regions from 3-D magnetic resonance (MR) images is
a crucial procedure for radiotherapy. Automatic delineation from 3-D whole volumes is in …
a crucial procedure for radiotherapy. Automatic delineation from 3-D whole volumes is in …
Deep active learning for automatic segmentation of maxillary sinus lesions using a convolutional neural network
The aim of this study was to segment the maxillary sinus into the maxillary bone, air, and
lesion, and to evaluate its accuracy by comparing and analyzing the results performed by …
lesion, and to evaluate its accuracy by comparing and analyzing the results performed by …
Active learning for accuracy enhancement of semantic segmentation with CNN-corrected label curations: Evaluation on kidney segmentation in abdominal CT
Segmentation is fundamental to medical image analysis. Recent advances in fully
convolutional networks has enabled automatic segmentation; however, high labeling efforts …
convolutional networks has enabled automatic segmentation; however, high labeling efforts …
Magnetic resonance imaging contrast enhancement synthesis using cascade networks with local supervision
Purpose Gadolinium‐based contrast agents (GBCAs) are widely administrated in MR
imaging for diagnostic studies and treatment planning. Although GBCAs are generally …
imaging for diagnostic studies and treatment planning. Although GBCAs are generally …
Combining natural and artificial intelligence for robust automatic anatomy segmentation: Application in neck and thorax auto‐contouring
JK Udupa, T Liu, C Jin, L Zhao, D Odhner… - Medical …, 2022 - Wiley Online Library
Background Automatic segmentation of 3D objects in computed tomography (CT) is
challenging. Current methods, based mainly on artificial intelligence (AI) and end‐to‐end …
challenging. Current methods, based mainly on artificial intelligence (AI) and end‐to‐end …
Detection of microaneurysms in fundus images based on an attention mechanism
L Zhang, S Feng, G Duan, Y Li, G Liu - Genes, 2019 - mdpi.com
Microaneurysms (MAs) are the earliest detectable diabetic retinopathy (DR) lesions. Thus,
the ability to automatically detect MAs is critical for the early diagnosis of DR. However …
the ability to automatically detect MAs is critical for the early diagnosis of DR. However …