CAD Lung Cancer Detection And Classification In CT
Qiang Li
Radiologyduke University
Grant 7R01CA113870-03 from National Cancer Institute, IRG: BMIT
Abstract: Early detection and diagnosis of lung cancer are very important because they may lead to an improved prognosis for lung cancer patients. Our goal in this project is to develop and evaluate an integrated interactive computer-aided diagnostic (CAD) scheme for early detection and diagnosis of lung cancer in multi-slice computed tomography (CT), which will incorporate a detection scheme and a diagnosis scheme into a clinically oriented system. The integration of the two CAD schemes will provide radiologists with a highly practical and convenient diagnostic environment, and it will also provide technically improved reliability and compactness compared with the use of two separate CAD schemes. The interaction between radiologists and a CAD scheme enables radiologists to correct the computer´s detection errors, such as to identify cancers missed by the computer, and to ignore most of the non-nodules incorrectly detected by the computer. As a result, it is expected that radiologists would become more accurate and productive in both detection and diagnosis of lung cancers by use of the integrated CAD scheme. Many innovative techniques and schemes are to be developed in this project, including (1) an accurate segmentation technique based on spiral scanning and dynamic programming; (2) an automated rule-based classifier using multiple composite features with minimized overtraining effects; (3) a nodule detection scheme using the nodule segmentation technique, the automated rule-based classifier, and a selective nodule enhancement filter; (4) a three-category nodule diagnosis scheme for distinguishing cancers from benign nodules and nonnodules; and (5) integration of the detection and diagnosis schemes, with the capability of interaction between the CAD scheme and its users. It is anticipated that the computerized detection scheme will detect 90% of nodules, with less than 4 non-nodules per CT scan, and that the diagnosis scheme will achieve an Az value (area under the receiver operating characteristic curve) of 0.90 or higher for distinction between cancers and non-cancers. Finally, an observer performance study will be conducted with 20 participating radiologists to examine the clinical usefulness of the integrated interactive CAD scheme. It is expected from the observer study that radiologists would significantly improve their detection and diagnosis accuracy for lung cancer with the aid of the interactive CAD scheme
Keywords: classification, health science profession, lung, neoplasm /cancer, radiology computer, diagnosis clinical research
Project start date: 2006-08-01
Project end date: 2009-07-31
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Grants awarded to Qiang Li
CAD Lung Cancer Detection And Classification In CT
Qiang Li
Radiologyduke University
Grant 7R01CA113870-03 from National Cancer Institute, IRG: BMIT
Abstract: Early detection and diagnosis of lung cancer are very important because they may lead to an improved prognosis for lung cancer patients. Our goal in this project is to develop and evaluate an integrated interactive computer-aided diagnostic (CAD) scheme for early detection and diagnosis of lung cancer in multi-slice computed tomography (CT), which will incorporate a detection scheme and a diagnosis scheme into a clinically oriented system. The integration of the two CAD schemes will provide radiologists with a highly practical and convenient diagnostic environment, and it will also provide technically improved reliability and compactness compared with the use of two separate CAD schemes. The interaction between radiologists and a CAD scheme enables radiologists to correct the computer´s detection errors, such as to identify cancers missed by the computer, and to ignore most of the non-nodules incorrectly detected by the computer. As a result, it is expected that radiologists would become more accurate and productive in both detection and diagnosis of lung cancers by use of the integrated CAD scheme. Many innovative techniques and schemes are to be developed in this project, including (1) an accurate segmentation technique based on spiral scanning and dynamic programming; (2) an automated rule-based classifier using multiple composite features with minimized overtraining effects; (3) a nodule detection scheme using the nodule segmentation technique, the automated rule-based classifier, and a selective nodule enhancement filter; (4) a three-category nodule diagnosis scheme for distinguishing cancers from benign nodules and nonnodules; and (5) integration of the detection and diagnosis schemes, with the capability of interaction between the CAD scheme and its users. It is anticipated that the computerized detection scheme will detect 90% of nodules, with less than 4 non-nodules per CT scan, and that the diagnosis scheme will achieve an Az value (area under the receiver operating characteristic curve) of 0.90 or higher for distinction between cancers and non-cancers. Finally, an observer performance study will be conducted with 20 participating radiologists to examine the clinical usefulness of the integrated interactive CAD scheme. It is expected from the observer study that radiologists would significantly improve their detection and diagnosis accuracy for lung cancer with the aid of the interactive CAD scheme
Keywords: classification, health science profession, lung, neoplasm /cancer, radiology computer, diagnosis clinical research
Project start date: 2006-08-01
Project end date: 2009-07-31
5R01CA113870-02 (2007): $198235
1R01CA113870-01A2 (2006): $204155
DETECTION OF HYBRIDIZATION WITHOUT RADIOACTIVE LABEL
Qiang Li
Adelphi Technology, Inc. 981-b Industrial Rd San Carlos, Ca 94070
Grant 1R43CA062638-01 from National Cancer Institute, IRG: ZRG7
Abstract: A novel surface phenomenon will be explored for the quantitative detection of nucleic acid hybridization. We will construct a relatively inexpensive instrument, which can attain a sensitivity limit comparable to the existing methodologies, without the use of dyes, or radioisotopes. As part of the phase l research, we will use the existing hardware to test affinity of DNA to a specifically prepared surface. This test is a necessary step in the operation of the instrument. We will also measure the binding of the complementary DNA to assess the detection limit, sensitivity and the issue of non-specific binding. In Phase Il, the signal to noise ratio will be optimized and a prototype of the device specifically designed for hybridization detection will be built. The complete hybridization protocol will be tested on the new instrument. If the proposed research is successful, the new instrument can perform routine nucleic acid hybridization detection for molecular biology research and clinical laboratory tests.
Keywords: biomedical equipment development, nucleic acid hybridization, surface property
Project start date: 1993-08-04
Project end date: 1994-03-31
1R43CA062638-01 (1993): $50000
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