journal article·2024Open access

Advancing Breast Cancer Diagnosis: The Development and Validation of the HERA-Net Model for Thermographic Analysis

S. Ramacharan, Martin Margala, Amjan Shaik, Prasun Chakrabarti, Tulika Chakrabarti

Computers, Materials & Continua· Volume 81· Issue 3

Abstract

Breast cancer remains a significant global health concern, with early detection being crucial for effective treatment and improved survival rates. This study introduces HERA-Net (Hybrid Extraction and Recognition Architecture... | Find, read and cite all the research you need on Tech Science Press
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Infrared Thermography in Medicine · Thermography and Photoacoustic Techniques

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

References (41)

Show source-provided references
1. A hybrid dependable deep feature extraction and ensemble-based machine learning approach for breast cancer detection10.1109/ACCESS.2023.3304628 ↗
2. Detection and classification of breast cancer using CNN
3. Temporal mammogram image registration using optimized curvilinear coordinates10.1016/j.cmpb.2016.01.019 ↗
4. All Cancer
5. A grey wolf-based method for mammographic mass classification10.3390/app10238422 ↗
6. Automated mammogram breast cancer detection using the optimized combination of convolutional and recurrent neural network10.1007/s12065-020-00403-x ↗
7. Image processing as an auxiliary methodology for analysis of thermograms
8. Breast tumor localization using skin surface temperatures from a 2D anatomic model without knowledge of the thermophysical properties10.1016/j.cmpb.2019.02.004 ↗
9. Breast cancer diagnosis using thermography and convolutional neural networks10.1016/j.mehy.2019.109542 ↗
10. Automatic image segmentation method for breast cancer analysis using thermography
11. Thermography based breast cancer detection using texture features and support vector machine10.1007/s10916-010-9611-z ↗
12. Lossless embedding using pixel differences and histogram shifting technique
13. Breast cancer detection using infrared thermal imaging and a deep learning model10.3390/s18092799 ↗
14. Laparoscopic detection and resection of occult liver tumors of multiple cancer types using real-time near-infrared fluorescence guidance10.1007/s00464-016-5007-6 ↗
15. Breast cancer identification via thermography image segmentation with a gradient vector flow and a convolutional neural network10.1155/2019/9807619 ↗
16. Breast cancer early detection: A phased approach to implementation10.1002/cncr.32887 ↗
17. An integrated index for breast cancer identification using histogram of oriented gradient and kernel locality preserving projection features extracted from Thermal images10.1080/17686733.2016.1176734 ↗
18. Inception-v4, inception-ResNet and the impact of residual connections on learning
19. DMI Visual Lab, “Deep learning model interpretability,” Accessed: Oct. 12, 2023. [Online]. Available: https://visual.ic.uff.br/dmi/
20. Breast cancer diagnosis in thermography using pre-trained VGG16 with deep attention mechanisms10.3390/sym15030582 ↗
21. Breast cancer detection and prevention using machine learning10.3390/diagnostics13193113 ↗
22. Detection of breast cancer using infrared thermal images for improved accuracy by using random forest and multilayer perceptron
23. Breast cancer detection based on thermographic images using machine learning and deep learning algorithms10.33545/26633582.2022.v4.i1a.68 ↗
24. Deep learning model for fully automated breast cancer detection system from thermograms10.1371/journal.pone.0262349 ↗
25. Thermal-based early breast cancer detection using inception V3, inception V4 and modified inception MV410.1007/s00521-021-06372-1 ↗
26. Breast cancer-caps: A breast cancer screening system based on capsule network utilizing the multiview breast thermal infrared images
27. Z. Mobarak, S. Hamida, N. Akouz, B. Cherradi, H. Nhaila and M. El Khaili, “Deep learning technique for classification of breast cancer using ultrasound images,” 2023. doi: 10.1109/IRASET57153.2023.10153069.10.1109/IRASET57153.2023.10153069 ↗
28. Breast cancer detection using deep learning: An investigation using the DDSM dataset and a customized AlexNet and support vector machine10.1109/ACCESS.2023.3311892 ↗
29. Breast cancer classification based on convolutional neural network and image fusion approaches using ultrasound images
30. Realization of the contrast limited adaptive histogram equalization (CLAHE) for real time image enhancement10.1023/B:VLSI.0000028532.53893.82 ↗
31. An objective method to identify optimum clip-limit and histogram specification of contrast limited adaptive histogram equalization for MR images10.1016/j.bbe.2016.11.006 ↗
32. A low-memory, straightforward and fast bilateral filter through subsampling in spatial domain10.1111/j.1467-8659.2011.02078.x ↗
33. Kumar · Image Processing in Diabetic Related Causes · 201610.1007/978-981-287-624-9 ↗
34. Comparing LBP, HOG and deep features for classification of histopathology images
35. Retrieve content images using color histogram, LBP and HOG
36. O. Ronneberger, P. Fischer, and T. Brox, “U-Net: Convolutional networks for biomedical image segmentation,” 2015, arXiv:1505.04597.10.1007/978-3-319-24574-4_28 ↗
37. E. Pm, “Enhanced VGG-19 model for accurate brain tumor prediction,” 2023. doi: 10.1109/NMITCON58196.2023.10276235.10.1109/NMITCON58196.2023.10276235 ↗
38. Fundus image classification using VGG-19 architecture with PCA and SVD
39. A survey of convolutional neural network in breast cancer
40. Thermogram adaptive efficient model for breast cancer detection using fractional derivative mask and hybrid feature set in the IoT environment
41. BUS-BRA: A breast ultrasound dataset for assessing computer-aided diagnosis systems