Towards machine learning-aided lung cancer clinical routines: Approaches and open challenges
Advancements in the development of computer-aided decision (CAD) systems for clinical
routines provide unquestionable benefits in connecting human medical expertise with …
routines provide unquestionable benefits in connecting human medical expertise with …
CariesNet: a deep learning approach for segmentation of multi-stage caries lesion from oral panoramic X-ray image
Dental caries has been a common health issue throughout the world, which can even lead
to dental pulp and root apical inflammation eventually. Timely and effective treatment of …
to dental pulp and root apical inflammation eventually. Timely and effective treatment of …
Towards more precise automatic analysis: a comprehensive survey of deep learning-based multi-organ segmentation
X Liu, L Qu, Z Xie, J Zhao, Y Shi, Z Song - arXiv preprint arXiv:2303.00232, 2023 - arxiv.org
Accurate segmentation of multiple organs of the head, neck, chest, and abdomen from
medical images is an essential step in computer-aided diagnosis, surgical navigation, and …
medical images is an essential step in computer-aided diagnosis, surgical navigation, and …
Teeth U-Net: A segmentation model of dental panoramic X-ray images for context semantics and contrast enhancement
S Hou, T Zhou, Y Liu, P Dang, H Lu, H Shi - Computers in Biology and …, 2023 - Elsevier
Background and objective It is very significant in orthodontics and restorative dentistry that
the teeth are segmented from dental panoramic X-ray images. Nevertheless, there are some …
the teeth are segmented from dental panoramic X-ray images. Nevertheless, there are some …
A robust shape-aware rib fracture detection and segmentation framework with contrastive learning
The rib fracture is a common type of thoracic skeletal trauma, and its inspections using
computed tomography (CT) scans are critical for clinical evaluation and treatment planning …
computed tomography (CT) scans are critical for clinical evaluation and treatment planning …
A statistical deformation model-based data augmentation method for volumetric medical image segmentation
The accurate delineation of organs-at-risk (OARs) is a crucial step in treatment planning
during radiotherapy, as it minimizes the potential adverse effects of radiation on surrounding …
during radiotherapy, as it minimizes the potential adverse effects of radiation on surrounding …
[HTML][HTML] A deep learning approach for detecting colorectal cancer via Raman spectra
Abstract Objective and Impact Statement. Distinguishing tumors from normal tissues is vital
in the intraoperative diagnosis and pathological examination. In this work, we propose to …
in the intraoperative diagnosis and pathological examination. In this work, we propose to …
Multi-scale graph learning for ovarian tumor segmentation from ct images
Ovarian cancer is the gynecological malignant tumor with low early diagnosis rate and high
mortality. Automated and reliable segmentation of ovarian tumor plays an essential role in …
mortality. Automated and reliable segmentation of ovarian tumor plays an essential role in …
An n-sigmoid activation function to improve the squeeze-and-excitation for 2D and 3D deep networks
DB Mulindwa, S Du - Electronics, 2023 - mdpi.com
The Squeeze-and-Excitation (SE) structure has been designed to enhance the neural
network performance by allowing it to execute positive channel-wise feature recalibration …
network performance by allowing it to execute positive channel-wise feature recalibration …
Fully automated multiorgan segmentation of female pelvic magnetic resonance images with coarse‐to‐fine convolutional neural network
F Zabihollahy, AN Viswanathan, EJ Schmidt… - Medical …, 2021 - Wiley Online Library
Purpose Brachytherapy combined with external beam radiotherapy (EBRT) is the standard
treatment for cervical cancer and has been shown to improve overall survival rates …
treatment for cervical cancer and has been shown to improve overall survival rates …