Deep learning in breast cancer imaging: A decade of progress and future directions
Breast cancer has reached the highest incidence rate worldwide among all malignancies
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …
Cancer prognosis and diagnosis methods based on ensemble learning
Ensemble methods try to improve performance via integrating different kinds of input data,
features, or learning algorithms. In addition to other areas, they are finding their applications …
features, or learning algorithms. In addition to other areas, they are finding their applications …
AAU-net: an adaptive attention U-net for breast lesions segmentation in ultrasound images
Various deep learning methods have been proposed to segment breast lesions from
ultrasound images. However, similar intensity distributions, variable tumor morphologies …
ultrasound images. However, similar intensity distributions, variable tumor morphologies …
Rethinking the unpretentious U-net for medical ultrasound image segmentation
Breast tumor segmentation from ultrasound images is one of the key steps that help us
characterize and localize tumor regions. However, variable tumor morphology, blurred …
characterize and localize tumor regions. However, variable tumor morphology, blurred …
Multi-region radiomics for artificially intelligent diagnosis of breast cancer using multimodal ultrasound
Z Xu, Y Wang, M Chen, Q Zhang - Computers in Biology and Medicine, 2022 - Elsevier
Purpose The ultrasound (US) diagnosis of breast cancer is usually based on a single-region
of a whole breast tumor from a single ultrasonic modality, which limits the diagnostic …
of a whole breast tumor from a single ultrasonic modality, which limits the diagnostic …
Fusion of transfer learning models with LSTM for detection of breast cancer using ultrasound images
MG Lanjewar, KG Panchbhai, LB Patle - Computers in Biology and …, 2024 - Elsevier
Breast Cancer (BC) is one of the top reasons for fatality in women worldwide. As a result,
timely identification is critical for successful therapy and excellent survival rates. Transfer …
timely identification is critical for successful therapy and excellent survival rates. Transfer …
Federated learning aided breast cancer detection with intelligent Heuristic-based deep learning framework
S Kumbhare, AB Kathole, S Shinde - Biomedical Signal Processing and …, 2023 - Elsevier
Breast cancer is the second largest cause of female cancer death and one of the most
hazardous diseases that leads to a higher mortality rate. One of the eminent medical …
hazardous diseases that leads to a higher mortality rate. One of the eminent medical …
Ultrasound radiomics in personalized breast management: Current status and future prospects
J Gu, T Jiang - Frontiers in oncology, 2022 - frontiersin.org
Breast cancer is the most common cancer in women worldwide. Providing accurate and
efficient diagnosis, risk stratification and timely adjustment of treatment strategies are …
efficient diagnosis, risk stratification and timely adjustment of treatment strategies are …
Recent advances in machine learning applied to ultrasound imaging
M Micucci, A Iula - Electronics, 2022 - mdpi.com
Machine learning (ML) methods are pervading an increasing number of fields of application
because of their capacity to effectively solve a wide variety of challenging problems. The …
because of their capacity to effectively solve a wide variety of challenging problems. The …
A review on computational methods for breast cancer detection in ultrasound images using multi-image modalities
S Sushanki, AK Bhandari, AK Singh - Archives of Computational Methods …, 2024 - Springer
Breast cancer is a kind of cancer that develops and propagates from tissues of the breast
and slowly transcends the whole body, this type of tumor is found in both sexes. Early …
and slowly transcends the whole body, this type of tumor is found in both sexes. Early …