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Practical utility of liver segmentation methods in clinical surgeries and interventions
Clinical imaging (eg, magnetic resonance imaging and computed tomography) is a crucial
adjunct for clinicians, aiding in the diagnosis of diseases and planning of appropriate …
adjunct for clinicians, aiding in the diagnosis of diseases and planning of appropriate …
Timedistributed-cnn-lstm: A hybrid approach combining cnn and lstm to classify brain tumor on 3d mri scans performing ablation study
Identification of brain tumors at an early stage is crucial in cancer diagnosis, as a timely
diagnosis can increase the chances of survival. Considering the challenges of tumor …
diagnosis can increase the chances of survival. Considering the challenges of tumor …
Deep learning-based medical images segmentation of musculoskeletal anatomical structures: a survey of bottlenecks and strategies
By leveraging the recent development of artificial intelligence algorithms, several medical
sectors have benefited from using automatic segmentation tools from bioimaging to segment …
sectors have benefited from using automatic segmentation tools from bioimaging to segment …
MS-FANet: multi-scale feature attention network for liver tumor segmentation
Y Chen, C Zheng, W Zhang, H Lin, W Chen… - Computers in biology …, 2023 - Elsevier
Accurate segmentation of liver tumors is a prerequisite for early diagnosis of liver cancer.
Segmentation networks extract features continuously at the same scale, which cannot adapt …
Segmentation networks extract features continuously at the same scale, which cannot adapt …
Multi-depth fusion network for whole-heart CT image segmentation
Obtaining precise whole-heart segmentation from computed tomography (CT) or other
imaging techniques is prerequisite to clinically analyze the cardiac status, which plays an …
imaging techniques is prerequisite to clinically analyze the cardiac status, which plays an …
Canal-Net for automatic and robust 3D segmentation of mandibular canals in CBCT images using a continuity-aware contextual network
The purpose of this study was to propose a continuity-aware contextual network (Canal-Net)
for the automatic and robust 3D segmentation of the mandibular canal (MC) with high …
for the automatic and robust 3D segmentation of the mandibular canal (MC) with high …
A deep residual attention-based U-Net with a biplane joint method for liver segmentation from CT scans
Y Chen, C Zheng, T Zhou, L Feng, L Liu, Q Zeng… - Computers in Biology …, 2023 - Elsevier
Liver tumours are diseases with high morbidity and high deterioration probabilities, and
accurate liver area segmentation from computed tomography (CT) scans is a prerequisite for …
accurate liver area segmentation from computed tomography (CT) scans is a prerequisite for …
X-ray microscopy enables multiscale high-resolution 3D imaging of plant cells, tissues, and organs
Capturing complete internal anatomies of plant organs and tissues within their relevant
morphological context remains a key challenge in plant science. While plant growth and …
morphological context remains a key challenge in plant science. While plant growth and …
Longitudinal deep network for consistent OCT layer segmentation
Retinal layer thickness is an important bio-marker for people with multiple sclerosis (PwMS).
In clinical practice, retinal layer thickness changes in optical coherence tomography (OCT) …
In clinical practice, retinal layer thickness changes in optical coherence tomography (OCT) …
[HTML][HTML] Effect of childhood atropine treatment on adult choroidal thickness using sequential deep learning-enabled segmentation
Purpose To describe choroidal thickness measurements using a sequential deep learning
segmentation in adults who received childhood atropine treatment for myopia control …
segmentation in adults who received childhood atropine treatment for myopia control …