Lung Cancer prediction using machine learning: A comprehensive approach

SS Raoof, MA Jabbar… - 2020 2nd International …, 2020 - ieeexplore.ieee.org
The prominent cause of cancer-related mortality throughout the globe is “Lung Cancer”.
Hence beforehand detection, prediction and diagnosis of lung cancer has become essential …

Transfer learning for medical images analyses: A survey

X Yu, J Wang, QQ Hong, R Teku, SH Wang, YD Zhang - Neurocomputing, 2022 - Elsevier
The advent of deep learning has brought great change to the community of computer
science and also revitalized numerous fields where traditional machine learning methods …

Deep learning for image-based cancer detection and diagnosis− A survey

Z Hu, J Tang, Z Wang, K Zhang, L Zhang, Q Sun - Pattern Recognition, 2018 - Elsevier
In this paper, we aim to provide a survey on the applications of deep learning for cancer
detection and diagnosis and hope to provide an overview of the progress in this field. In the …

[PDF][PDF] Deep Learning-Based Cancer Detection-Recent Developments, Trend and Challenges.

G Kumar, H Alqahtani - CMES-Computer Modeling in …, 2022 - cdn.techscience.cn
Cancer is one of the most critical diseases that has caused several deaths in today's world.
In most cases, doctors and practitioners are only able to diagnose cancer in its later stages …

Dual focal loss to address class imbalance in semantic segmentation

MS Hossain, JM Betts, AP Paplinski - Neurocomputing, 2021 - Elsevier
A common problem in pixelwise classification or semantic segmentation is class imbalance,
which tends to reduce the classification accuracy of minority-class regions. An effective way …

PSNet: prostate segmentation on MRI based on a convolutional neural network

Z Tian, L Liu, Z Zhang, B Fei - Journal of medical imaging, 2018 - spiedigitallibrary.org
Automatic segmentation of the prostate on magnetic resonance images (MRI) has many
applications in prostate cancer diagnosis and therapy. We proposed a deep fully …

[HTML][HTML] Automatic segmentation of prostate MRI using convolutional neural networks: Investigating the impact of network architecture on the accuracy of volume …

N Ghavami, Y Hu, E Gibson, E Bonmati… - Medical image …, 2019 - Elsevier
Convolutional neural networks (CNNs) have recently led to significant advances in
automatic segmentations of anatomical structures in medical images, and a wide variety of …

Anisotropic 3D multi-stream CNN for accurate prostate segmentation from multi-planar MRI

A Meyer, G Chlebus, M Rak, D Schindele… - Computer Methods and …, 2021 - Elsevier
Abstract Background and Objective: Accurate and reliable segmentation of the prostate
gland in MR images can support the clinical assessment of prostate cancer, as well as the …

Systems and methods for rapid neural network-based image segmentation and radiopharmaceutical uptake determination

KV Sjöstrand, JFA Richter, KEM Johnsson… - US Patent …, 2021 - Google Patents
First worldwide family litigation filed litigation https://patents. darts-ip. com/? family=
67140292&utm_source= google_patent&utm_medium= platform_link&utm_campaign …

Technical considerations for semantic segmentation in MRI using convolutional neural networks

AD Desai, GE Gold, BA Hargreaves… - arxiv preprint arxiv …, 2019 - arxiv.org
High-fidelity semantic segmentation of magnetic resonance volumes is critical for estimating
tissue morphometry and relaxation parameters in both clinical and research applications …