A review on the application of deep learning for CT reconstruction, bone segmentation and surgical planning in oral and maxillofacial surgery
J Minnema, A Ernst, M van Eijnatten… - Dentomaxillofacial …, 2022 - academic.oup.com
Computer-assisted surgery (CAS) allows clinicians to personalize treatments and surgical
interventions and has therefore become an increasingly popular treatment modality in …
interventions and has therefore become an increasingly popular treatment modality in …
CT‐based automatic spine segmentation using patch‐based deep learning
CT vertebral segmentation plays an essential role in various clinical applications, such as
computer‐assisted surgical interventions, assessment of spinal abnormalities, and vertebral …
computer‐assisted surgical interventions, assessment of spinal abnormalities, and vertebral …
Breast cancer classification from histopathological images using patch-based deep learning modeling
Accurate detection and classification of breast cancer is a critical task in medical imaging
due to the complexity of breast tissues. Due to automatic feature extraction ability, deep …
due to the complexity of breast tissues. Due to automatic feature extraction ability, deep …
A lightweight convolutional neural network model for liver segmentation in medical diagnosis
Liver segmentation and recognition from computed tomography (CT) images is a warm topic
in image processing which is helpful for doctors and practitioners. Currently, many deep …
in image processing which is helpful for doctors and practitioners. Currently, many deep …
OP-convNet: a patch classification-based framework for CT vertebrae segmentation
Accurate vertebrae segmentation from medical images plays an important role in clinical
tasks of surgical planning, diagnosis, kyphosis, scoliosis, degenerative disc disease …
tasks of surgical planning, diagnosis, kyphosis, scoliosis, degenerative disc disease …
SVseg: Stacked sparse autoencoder-based patch classification modeling for vertebrae segmentation
Precise vertebrae segmentation is essential for the image-related analysis of spine
pathologies such as vertebral compression fractures and other abnormalities, as well as for …
pathologies such as vertebral compression fractures and other abnormalities, as well as for …
[Retracted] Efficient Liver Segmentation from Computed Tomography Images Using Deep Learning
M Ahmad, SF Qadri, MU Ashraf, K Subhi… - Computational …, 2022 - Wiley Online Library
Segmentation of a liver in computed tomography (CT) images is an important step toward
quantitative biomarkers for a computer‐aided decision support system and precise medical …
quantitative biomarkers for a computer‐aided decision support system and precise medical …
Skin lesion classification by ensembles of deep convolutional networks and regularly spaced shifting
K Thurnhofer-Hemsi, E López-Rubio… - IEEE …, 2021 - ieeexplore.ieee.org
Skin lesions are caused due to multiple factors, like allergies, infections, exposition to the
sun, etc. These skin diseases have become a challenge in medical diagnosis due to visual …
sun, etc. These skin diseases have become a challenge in medical diagnosis due to visual …
Deep belief network modeling for automatic liver segmentation
The liver segmentation in CT scan images is a significant step toward the development of a
quantitative biomarker for computer-aided diagnosis. In this paper, we propose an automatic …
quantitative biomarker for computer-aided diagnosis. In this paper, we propose an automatic …
Recent advancements and future prospects in active deep learning for medical image segmentation and classification
Medical images are helpful for the diagnosis, treatment, and evaluation of diseases. Precise
medical image segmentation improves diagnosis and decision-making, aiding intelligent …
medical image segmentation improves diagnosis and decision-making, aiding intelligent …