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[HTML][HTML] Federated and transfer learning methods for the classification of Melanoma and Nonmelanoma skin cancers: a prospective study
Skin cancer is considered a dangerous type of cancer with a high global mortality rate.
Manual skin cancer diagnosis is a challenging and time-consuming method due to the …
Manual skin cancer diagnosis is a challenging and time-consuming method due to the …
Revolutionizing tumor detection and classification in multimodality imaging based on deep learning approaches: Methods, applications and limitations
BACKGROUND: The emergence of deep learning (DL) techniques has revolutionized tumor
detection and classification in medical imaging, with multimodal medical imaging (MMI) …
detection and classification in medical imaging, with multimodal medical imaging (MMI) …
Multiscale adaptive and attention-dilated convolutional neural network for efficient leukemia detection model with multiscale trans-res-Unet3+-based segmentation …
K Gokulkannan, TA Mohanaprakash… - … Signal Processing and …, 2024 - Elsevier
A precise early-stage leukemia diagnosis is essential for treating patients and saving their
lives. The least expensive way for the initial diagnosis of leukemia in patients is the …
lives. The least expensive way for the initial diagnosis of leukemia in patients is the …
Ghost-ResNeXt: An effective deep learning based on mature and immature WBC classification
White blood cells (WBCs) must be evaluated to determine how well the human immune
system performs. Abnormal WBC counts may indicate malignancy, tuberculosis, severe …
system performs. Abnormal WBC counts may indicate malignancy, tuberculosis, severe …
Segmentation of white blood cells based on CBAM-DC-UNet
D Li, S Yin, Y Lei, J Qian, C Zhao, L Zhang - IEEE Access, 2022 - ieeexplore.ieee.org
Monitoring the morphology of blood leukocytes, plays an important role in medical research,
especially in the treatment of diseases such as immunodeficiency. Traditional manual …
especially in the treatment of diseases such as immunodeficiency. Traditional manual …
An intelligent white blood cell detection and multi-class classification using fine optimal DCRNet
PR Krishna Prasad, ES Reddy… - Multimedia Tools and …, 2024 - Springer
The major goal of this research is to develop a Deep Learning (DL) based automatic
identification and classification of white blood cells (WBCs) with high accuracy and …
identification and classification of white blood cells (WBCs) with high accuracy and …
Bone marrow cancer detection from leukocytes using neural networks
In this ambitious project, the primary goal is to harness the power of cutting-edge neural
networks, specifically ResNet50 and MobileNetV2, to discern between cancerous and …
networks, specifically ResNet50 and MobileNetV2, to discern between cancerous and …
[HTML][HTML] Recent Breakthroughs in PET-CT Multimodality Imaging: Innovations and Clinical Impact
This review presents a detailed examination of the most recent advancements in positron
emission tomography–computed tomography (PET-CT) multimodal imaging over the past …
emission tomography–computed tomography (PET-CT) multimodal imaging over the past …
An XAI integrated identification system of white blood cell type using variants of vision transformer
Abstract White Blood Cells (WBCs) serve as one of the primary defense mechanisms
against various diseases. Therefore, in order to detect blood cancer as well as many other …
against various diseases. Therefore, in order to detect blood cancer as well as many other …
Nucleus segmentation of white blood cells in blood smear images by modeling the pixels' intensities as a set of three Gaussian distributions
The precise segmentation of white blood cells (WBCs) within blood smear images is a
significant challenge with implications for both medical research and image processing. Of …
significant challenge with implications for both medical research and image processing. Of …