Dr. Maryellen L. Giger
A. N. Pritzker Professor Radiology/Medical Physics at Univ of Chicago
SPIE Involvement:
| Board of Directors | Compensation Committee | Diversity and Inclusion Ad Hoc Committee | Executive Committee | Nominating Committee | Publications Committee | Strategic Planning Committee | Fellow status | Conference Program Committee | Symposium Chair | Conference Chair | Journal Editorial Board Member | Author | Instructor | Student Chapter Advisor
Area of Expertise:
computer-aided diagnosis , computerized lesion detection , digital medical imaging , quantitative image analysis , reader/observer ROC studies , digital image analysis
Publications (127)

SPIE Journal Paper | November 10, 2018
JMI Vol. 5 Issue 04
KEYWORDS: Prostate, Magnetic resonance imaging, Cancer, Prostate cancer, Biopsy, Image classification, Magnetism, Image processing, Medical imaging, Medical research

SPIE Journal Paper | August 21, 2018
JMI Vol. 6 Issue 01
KEYWORDS: Magnetic resonance imaging, Breast, Image classification, Magnetism, Feature extraction, RGB color model, Tumors, 3D image processing, Tumor growth modeling, Convolutional neural networks

PROCEEDINGS ARTICLE | July 6, 2018
Proc. SPIE. 10718, 14th International Workshop on Breast Imaging (IWBI 2018)
KEYWORDS: Cancer, Breast cancer, Magnetic resonance imaging, Feature extraction, Biopsy

PROCEEDINGS ARTICLE | July 6, 2018
Proc. SPIE. 10718, 14th International Workshop on Breast Imaging (IWBI 2018)
KEYWORDS: Breast, Statistical analysis, Computer aided diagnosis and therapy, Breast cancer, Tumors, Feature extraction, Medical imaging, Mammography, Image classification

PROCEEDINGS ARTICLE | March 12, 2018
Proc. SPIE. 10578, Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging
KEYWORDS: Statistical analysis, Tumor growth modeling, Cancer, Modulation, Tissues, Luminescence, Diagnostics, Control systems, Collagen, Fluorescence lifetime imaging

PROCEEDINGS ARTICLE | March 9, 2018
Proc. SPIE. 10573, Medical Imaging 2018: Physics of Medical Imaging
KEYWORDS: Convolutional neural networks, Imaging systems, Ionizing radiation, Diagnostics, Image acquisition, Feature extraction, Lung, Image quality, Machine learning, Computed tomography

Showing 5 of 127 publications
Conference Committee Involvement (19)
Computer-Aided Diagnosis
17 February 2019 | San Diego, California, United States
SPIE/COS Photonics Asia
11 October 2018 | Beijing, China
Computer-Aided Diagnosis
12 February 2018 | Houston, Texas, United States
Computer-Aided Diagnosis Posters
13 February 2017 | Orlando, FL, United States
Computer-Aided Diagnosis
13 February 2017 | Orlando, Florida, United States
Showing 5 of 19 published special sections
Course Instructor
SC356: Digital Mammography and Computer-Aided Diagnosis
The term Digital Mammography refers to the technology that is used for the electronic capture and display of x-ray images of the breast. In this process, film is not essential but it may be used as a recording medium for viewing and storing digital mammographic images. The various digital mammographic technologies are reviewed with emphasis on detector design and acquisition approach. These technologies include flat panel detectors using amorphous silicon detector arrays with a scintillator, flat panel amorphous selenium, stimulable phosphors, and slot scanning techniques using charge-coupled devices. Recent progress on advanced applications, such as tomographic and 3-D imaging of the breast, is presented. The interpretation of breast images can benefit from computer technology with advances in CAD. Computer-aided diagnosis (CAD) can be defined as a diagnosis made by a radiologist who uses the output from a computerized analysis of medical images as a second opinion in detecting lesions and in making diagnostic decisions. The final diagnosis is made by the radiologist. Rationale, computerized image analysis methods, and evaluation of performance of multi-modality CAD in the detection, diagnosis, and risk assessment of breast cancer will be reviewed.
SC882: Computer-Aided Diagnosis
The interpretation of medical images is expected to benefit from computer technology with advances in CAD. Computer-aided diagnosis (CAD) can be defined as a diagnosis made by a radiologist who uses the output from a computerized analysis of medical images as a second opinion in detecting lesions and in making diagnostic decisions. The final diagnosis is made by the radiologist. Rationale, computerized image analysis methods, evaluation methods, and translational clinical studies of CAD in the detection, diagnosis, and risk assessment of cancer will be reviewed. Specific examples will be presented in breast imaging, thoracic imaging, and colonography.
SIGN IN TO:
  • View contact details

UPDATE YOUR PROFILE
Is this your profile? Update it now.
Don’t have a profile and want one?

Back to Top