Artificial intelligence and machine learning in breast - ESR Connect

Research Presentation Session

RPS 702 - Artificial intelligence and machine learning in breast

  • 13 Lectures
  • 63 Minutes
  • 11 Speakers
  • 2 Comments

Lectures

1
RPS 702 - Leveraging ipsilateral dual-view information for mass detection in mammograms using deep learning

RPS 702 - Leveraging ipsilateral dual-view information for mass detection in mammograms using deep learning

03:41Ma Jie, Shenzhen / China

2
RPS 702 - Artificial intelligence-based breast density classifier improves mammography reporting reliability

RPS 702 - Artificial intelligence-based breast density classifier improves mammography reporting reliability

04:52A. Watanabe, Manhattan beach, CA / United States

3
RPS 702 - MRI-based radiomics for prediction to neoadjuvant chemotherapy in breast cancer: a referral centre analysis

RPS 702 - MRI-based radiomics for prediction to neoadjuvant chemotherapy in breast cancer: a referral centre analysis

04:56F. Pesapane, Milan / Italy

4
RPS 702 - Measuring short and long-term breast cancer risk by combining mammographic texture models, an AI-based CAD system, and established risk factors

RPS 702 - Measuring short and long-term breast cancer risk by combining mammographic texture models, an AI-based CAD system, and established risk factors

04:59A. Lauritzen, Copenhagen / Denmark

5
RPS 702 - Evaluation of 3T multiparametric MRI with radiomic analysis for differentiating benign and malignant breast lesions

RPS 702 - Evaluation of 3T multiparametric MRI with radiomic analysis for differentiating benign and malignant breast lesions

04:42A. Vamvakas, Larissa / Greece

6
RPS 702 - Diagnostic performance of AI for cancers registered in a mammography screening program: a retrospective analysis

RPS 702 - Diagnostic performance of AI for cancers registered in a mammography screening program: a retrospective analysis

04:34Y. Köylüoğlu, Istanbul / Turkey

7
RPS 702 - Radiomic machine learning for predicting prognostic biomarkers and molecular subtypes of breast cancer based on the integration of tumour heterogeneity and angiogenesis properties at MRI

RPS 702 - Radiomic machine learning for predicting prognostic biomarkers and molecular subtypes of breast cancer based on the integration of tumour heterogeneity and angiogenesis properties at MRI

06:24H. Park, Ansan / Korea, Republic of

8
RPS 702 - Radiomics analysis in breast MRI for non-invasive (in situ) breast cancer characterisation: initial results

RPS 702 - Radiomics analysis in breast MRI for non-invasive (in situ) breast cancer characterisation: initial results

03:42G. Lavazza, Turin / Italy

9
RPS 702 - Machine learning approaches for optimization in MRI texture analysis of breast cancer to predict prognostic biomarkers and molecular subtypes

RPS 702 - Machine learning approaches for optimization in MRI texture analysis of breast cancer to predict prognostic biomarkers and molecular subtypes

05:05H. Park, Ansan / Korea, Republic of

10
RPS 702 - DCE-MRI radiomics analysis for breast lesions characterisation

RPS 702 - DCE-MRI radiomics analysis for breast lesions characterisation

05:37M. Di Marco, Palermo / Italy

11
RPS 702 - Using AI to identify normal cases that may not need a second reader assessment in a French breast cancer screening program (BCSP): a retrospective evaluation

RPS 702 - Using AI to identify normal cases that may not need a second reader assessment in a French breast cancer screening program (BCSP): a retrospective evaluation

05:51H. Jarraya, Arras / France

12
RPS 702 - Comparison of artificial intelligence/machine learning algorithm in reporting computed radiography (CR) and digital radiography (DR) mammography studies

RPS 702 - Comparison of artificial intelligence/machine learning algorithm in reporting computed radiography (CR) and digital radiography (DR) mammography studies

04:42R. Ananthasivan, Bangalore / India

13
RPS 702 - Mammographic breast density assessment via deeply aggregating bilateral context information

RPS 702 - Mammographic breast density assessment via deeply aggregating bilateral context information

04:35Ma Jie, Shenzhen / China

Comments

Ma Milagrosa Garcia

March 4, 2021 | 07:05 CET

Thank you

Alexandros - Chrysovalantis Vamvakas

March 7, 2021 | 11:04 CET

You are welcome!

Speakers

Presenter

Ma Jie

Shenzhen, China

Presenter

Alyssa Watanabe

Manhattan Beach, United States

Presenter

Filippo Pesapane

Milan, Italy

Presenter

Andreas David Lauritzen

København, Denmark

Presenter

Alexandros-Chrysovalantis Vamvakas

Larisa, Greece

Presenter

Yılmaz Onat Köylüoğlu

Istanbul, Turkey

Presenter

Hyun Soo Park

Ansan, Korea, Republic of

Presenter

Giulia Lavazza

Torino, Italy

Presenter

Mariangela Di Marco

Palermo, Italy

Presenter

Hajer Jarraya

Lille, France

Presenter

Rupa Ananthasivan

Bangalore, India

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