Multimodal deep learning with feature level fusion for identification of choroidal neovascularization activity in age‐related macular degeneration
K **, Y Yan, M Chen, J Wang, X Pan, X Liu… - Acta …, 2022 - Wiley Online Library
Purpose This study aimed to determine the efficacy of a multimodal deep learning (DL)
model using optical coherence tomography (OCT) and optical coherence tomography …
model using optical coherence tomography (OCT) and optical coherence tomography …
Discriminative cervical lesion detection in colposcopic images with global class activation and local bin excitation
Accurate cervical lesion detection (CLD) methods using colposcopic images are highly
demanded in computer-aided diagnosis (CAD) for automatic diagnosis of High-grade …
demanded in computer-aided diagnosis (CAD) for automatic diagnosis of High-grade …
Deep evidential fusion network for medical image classification
The multi-modality characteristic of medical images calls for the application of information
fusion theory in computer aided diagnosis (CAD) algorithm design. Recently, the research of …
fusion theory in computer aided diagnosis (CAD) algorithm design. Recently, the research of …
IMIIN: An inter-modality information interaction network for 3D multi-modal breast tumor segmentation
Breast tumor segmentation is critical to the diagnosis and treatment of breast cancer. In
clinical breast cancer analysis, experts often examine multi-modal images since such …
clinical breast cancer analysis, experts often examine multi-modal images since such …
Multiple instance convolutional neural network with modality-based attention and contextual multi-instance learning pooling layer for effective differentiation between …
Malignant epithelial ovarian tumors (MEOTs) are the most lethal gynecologic malignancies,
accounting for 90% of ovarian cancer cases. By contrast, borderline epithelial ovarian …
accounting for 90% of ovarian cancer cases. By contrast, borderline epithelial ovarian …
Dual-attention EfficientNet based on multi-view feature fusion for cervical squamous intraepithelial lesions diagnosis
Y Guo, Y Wang, H Yang, J Zhang, Q Sun - Biocybernetics and Biomedical …, 2022 - Elsevier
Cervicograms are widely used in cervical cancer screening but exhibit a high misdiagnosis
rate. Even senior experts show only 48% specificity on clinical examinations. Most existing …
rate. Even senior experts show only 48% specificity on clinical examinations. Most existing …
Transferring Adult-like Phase Images for Robust Multi-view Isointense Infant Brain Segmentation
Accurate tissue segmentation of infant brain in magnetic resonance (MR) images is crucial
for charting early brain development and identifying biomarkers. Due to ongoing myelination …
for charting early brain development and identifying biomarkers. Due to ongoing myelination …
Contrastive learning for echocardiographic view integration
In this work, we aimed to tackle the challenge of fusing information from multiple
echocardiographic views, mimicking cardiologists making diagnoses with an integrative …
echocardiographic views, mimicking cardiologists making diagnoses with an integrative …
Multi-phase and multi-level selective feature fusion for automated pancreas segmentation from CT images
CT images scanned in arterial and venous phases have been demonstrated to provide
complementary information for accurate pancreas segmentation. In this paper, we propose a …
complementary information for accurate pancreas segmentation. In this paper, we propose a …
Collaborative learning of cross-channel clinical attention for radiotherapy-related esophageal fistula prediction from ct
Early prognosis of the radiotherapy-related esophageal fistula is of great significance in
making personalized stratification and optimal treatment plans for esophageal cancer (EC) …
making personalized stratification and optimal treatment plans for esophageal cancer (EC) …