:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Sydorskyi, Volodymyr
Format:	Preprint
Published:	2024
Subjects:	Image and Video Processing
Online Access:	https://arxiv.org/abs/2408.14521
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Lung nodule classification on CT scan patches using 3D convolutional neural networks
by: Sydorskyi, Volodymyr
Published: (2026)

Quantifying uncertainty in lung cancer segmentation with foundation models applied to mixed-domain datasets
by: Rangnekar, Aneesh, et al.
Published: (2024)

Improving ovarian cancer segmentation accuracy with transformers through AI-guided labeling
by: Rangnekar, Aneesh, et al.
Published: (2024)

Stress-testing cross-cancer generalizability of 3D nnU-Net for PET-CT tumor segmentation: multi-cohort evaluation with novel oesophageal and lung cancer datasets
by: Ghosh, Soumen, et al.
Published: (2025)

A multitask framework for automated interpretation of multi-frame right upper quadrant ultrasound in clinical decision support
by: Guo, Haiman, et al.
Published: (2026)

EXACT-Net:EHR-guided lung tumor auto-segmentation for non-small cell lung cancer radiotherapy
by: Hooshangnejad, Hamed, et al.
Published: (2024)

Random forest-based out-of-distribution detection for robust lung cancer segmentation
by: Rangnekar, Aneesh, et al.
Published: (2025)

Framework for lung CT image segmentation based on UNet++
by: Ziang, Hao, et al.
Published: (2025)

Tumor-anchored deep feature random forests for out-of-distribution detection in lung cancer segmentation
by: Rangnekar, Aneesh, et al.
Published: (2025)

Underestimation of lung regions on chest X-ray segmentation masks assessed by comparison with total lung volume evaluated on computed tomography
by: Bombiński, Przemysław, et al.
Published: (2024)

MRI lung lobe segmentation in pediatric cystic fibrosis patients using a recurrent neural network trained with publicly accessible CT datasets
by: Pusterla, Orso, et al.
Published: (2021)

Gut decisions based on the liver: A radiomics approach to boost colorectal cancer screening
by: Hinterberger, Anna, et al.
Published: (2025)

Rule-based outlier detection of AI-generated anatomy segmentations
by: Krishnaswamy, Deepa, et al.
Published: (2024)

Direct vascular territory segmentation on cerebral digital subtraction angiography
by: van der Sluijs, P. Matthijs, et al.
Published: (2025)

Boosting multiple sclerosis lesion segmentation through attention mechanism
by: Rondinella, Alessia, et al.
Published: (2023)

Reconstruction-free segmentation from undersampled k-space using transformers
by: Zhang, Yundi, et al.
Published: (2025)

Self-supervised learning improves robustness of deep learning lung tumor segmentation to CT imaging differences
by: Jiang, Jue, et al.
Published: (2024)

Rethinking domain generalization in medical image segmentation: One image as one domain
by: Hong, Jin, et al.
Published: (2025)

ConfLUNet: Multiple sclerosis lesion instance segmentation in presence of confluent lesions
by: Wynen, Maxence, et al.
Published: (2025)

Promptable cancer segmentation using minimal expert-curated data
by: Karam, Lynn, et al.
Published: (2025)

Shape-aware synthesis of pathological lung CT scans using CycleGAN for enhanced semi-supervised lung segmentation
by: Khiati, Rezkellah Noureddine, et al.
Published: (2024)

A plug-and-play framework for curvilinear structure segmentation based on a learned reconnecting regularization
by: Carneiro-Esteves, Sophie, et al.
Published: (2024)

Volumetric segmentation of muscle compartments using in vivo imaging and architectural validation in human finger flexors
by: Li, Yang
Published: (2025)

GOUHFI: a novel contrast- and resolution-agnostic segmentation tool for Ultra-High Field MRI
by: Fortin, Marc-Antoine, et al.
Published: (2025)

Attention-ResUNet and EfficientSASM-UNet: UNet based frameworks for Lung and Nodule segmentation
by: Abdullah, Muhammad, et al.
Published: (2025)

Pre-processing and quality control of large clinical CT head datasets for intracranial arterial calcification segmentation
by: Jin, Benjamin, et al.
Published: (2024)

autoPET IV challenge: Incorporating organ supervision and human guidance for lesion segmentation in PET/CT
by: Huang, Junwei, et al.
Published: (2025)

ASCHOPLEX encounters Dafne: a federated continuous learning project for the generalizability of the Choroid Plexus automatic segmentation
by: Visani, Valentina, et al.
Published: (2025)

A comparative analysis of deep learning models for lung segmentation on X-ray images
by: Hryniewska-Guzik, Weronika, et al.
Published: (2024)

Classification based deep learning models for lung cancer and disease using medical images
by: Chaddad, Ahmad, et al.
Published: (2025)

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder
by: Brattoli, Biagio, et al.
Published: (2025)

Rich-U-Net: A medical image segmentation model for fusing spatial depth features and capturing minute structural details
by: Fang, Zhuoyi, et al.
Published: (2026)

Automatic segmentation of Organs at Risk in Head and Neck cancer patients from CT and MRI scans
by: Quetin, Sébastien, et al.
Published: (2024)

Promptable segmentation with region exploration enables minimal-effort expert-level prostate cancer delineation
by: Yang, Junqing, et al.
Published: (2026)

Tumor aware recurrent inter-patient deformable image registration of computed tomography scans with lung cancer
by: Jiang, Jue, et al.
Published: (2024)

Length-scale study in deep learning prediction for non-small cell lung cancer brain metastasis
by: Zhou, Haowen, et al.
Published: (2024)

Experts' cognition-driven safe noisy labels learning for precise segmentation of residual tumor in breast cancer
by: Yang, Yongquan, et al.
Published: (2023)

IMIL: Interactive Medical Image Learning Framework
by: Rao, Adrit, et al.
Published: (2024)

A 28nm 0.22μJ/token memory-compute-intensity-aware CNN-Transformer accelerator with hybrid-attention-based layer-fusion and cascaded pruning for semantic-segmentation
by: Dong, Pingcheng, et al.
Published: (2025)

Extracting lung function-correlated information from CT-encoded static textures
by: Huang, Yu-Hua, et al.
Published: (2022)