[HTML][HTML] Federated and transfer learning methods for the classification of Melanoma and Nonmelanoma skin cancers: a prospective study

S Riaz, A Naeem, H Malik, RA Naqvi, WK Loh - Sensors, 2023 - mdpi.com
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 …

Revolutionizing tumor detection and classification in multimodality imaging based on deep learning approaches: Methods, applications and limitations

D Hussain, MA Al-Masni, M Aslam… - Journal of X-Ray …, 2024 - journals.sagepub.com
BACKGROUND: The emergence of deep learning (DL) techniques has revolutionized tumor
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 …

Ghost-ResNeXt: An effective deep learning based on mature and immature WBC classification

SSR Bairaboina, SR Battula - Applied Sciences, 2023 - mdpi.com
White blood cells (WBCs) must be evaluated to determine how well the human immune
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 …

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 …

Bone marrow cancer detection from leukocytes using neural networks

SM Shanmuga, P Bhambri - Computational Intelligence and …, 2024 - taylorfrancis.com
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 …

[HTML][HTML] Recent Breakthroughs in PET-CT Multimodality Imaging: Innovations and Clinical Impact

D Hussain, N Abbas, J Khan - Bioengineering, 2024 - pmc.ncbi.nlm.nih.gov
This review presents a detailed examination of the most recent advancements in positron
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

SM Dipto, MT Reza, MNJ Rahman, MZ Parvez… - Proceedings of the …, 2023 - Springer
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 …

Nucleus segmentation of white blood cells in blood smear images by modeling the pixels' intensities as a set of three Gaussian distributions

F Garcia-Lamont, A Lopez-Chau, J Cervantes… - Medical & Biological …, 2024 - Springer
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 …