6/11 Image-driven precision oncology for malignant gliomas: beyond cliché (최승원 교수/삼성서울병원 신경외과)

작성자
kaistsoftware
작성일
2020-06-09 10:27
조회
6804
  • 강사 : 최승원 교수 (삼성서울병원 신경외과) 
  • 일시 : 2020. 6. 11 (목) 17:00~18:30
Malignant gliomas are most common primary brain malignancy in adults. Despite some success stories of other solid tumors, the cure for these tumors is still pessimistic. One of major hurdles to conquer these tumors is their rarity, and another concern is their peculiar anatomic location which may hinder adequate sampling. Given enormous intra-tumor heterogeneity, molecular biomarkers are limited to fully represent the biologic activities of the entire tumor as they are usually derived from a single confined sub-region of the tumor. During past decades, genomic research much helped to comprehend tumor biology of malignant gliomas, however, failed to improve the clinical outcome regarding precision oncology. In other words, genomic information alone could not recapitulate the tumor evolution underneath the clinical progression, which implying the necessity of integrating multi-omics data.
In the light of clinical application, medical images are powerful tools and potentially represent underlying biologic activity of tumors. Imaging biomarkers are more versatile than molecular biomarkers considering several key challenges against malignant gliomas; they are non-invasive and free from sampling bias, thus reflecting the characteristics of the whole tumor. However, they also have some inherent weakness; data reproducibility and objectivity are main concerns accompanied by radiographic assessment. Radiomics, by converting medical images into high-dimensional data, has enabled us to transform the descriptive imaging features into the format of quantitative and objective data, thus contributing the evolution of image-driven data science. Another unsolved issue is their translational ability in terms of biological activity. Many have attempted to annotate the imaging phenotype with understandable molecular correlates, still robust association has not been elucidated.
Herein we present the basic principles of radiomics and introduce several key radiomic studies in the field of neuro-oncology. Future perspectives of radiomics study will be also discussed in this session.
전체 121
번호 제목 작성자 작성일 추천 조회
공지사항
2024년 봄학기 콜로퀴엄 일정 안내
kaistsoftware | 2024.02.21 | 추천 1 | 조회 3509
kaistsoftware 2024.02.21 1 3509
40
9/17 공간마케팅 (이현수 교수/연세대 실내건축학과)
kaistsoftware | 2020.09.16 | 추천 0 | 조회 7306
kaistsoftware 2020.09.16 0 7306
39
2020년 가을학기 콜로퀴엄 일정 안내
kaistsoftware | 2020.09.11 | 추천 0 | 조회 7337
kaistsoftware 2020.09.11 0 7337
38
6/25 Big data – AI Integration (황의종 교수/KAIST 전기및전자공학부)
kaistsoftware | 2020.06.24 | 추천 0 | 조회 7171
kaistsoftware 2020.06.24 0 7171
37
6/18 엑소브레인 자연어 분석 및 심층질의응답 기술 (김현기 박사/ETRI 인공지능연구소 언어지능연구실)
kaistsoftware | 2020.06.17 | 추천 0 | 조회 6930
kaistsoftware 2020.06.17 0 6930
36
6/11 Image-driven precision oncology for malignant gliomas: beyond cliché (최승원 교수/삼성서울병원 신경외과)
kaistsoftware | 2020.06.09 | 추천 0 | 조회 6804
kaistsoftware 2020.06.09 0 6804
35
5/28 User-Driven Generative Models (주재걸 교수/KAIST AI대학원)
kaistsoftware | 2020.05.25 | 추천 0 | 조회 7367
kaistsoftware 2020.05.25 0 7367
34
5/21 지능형 데이터 분석을 위한 인공지능 프레임워크 기술 및 응용 (정옥란 교수/가천대 AI•SW학부)
kaistsoftware | 2020.05.18 | 추천 0 | 조회 7587
kaistsoftware 2020.05.18 0 7587
33
5/14 Two huddles when deep neural networks meet the real world (이지형/성균관대 AI대학원)
kaistsoftware | 2020.05.09 | 추천 0 | 조회 6700
kaistsoftware 2020.05.09 0 6700
32
4/23 산업용 VR, AR, MR의 현재와 미래 (조근식/인하대 컴퓨터공학과)
kaistsoftware | 2020.04.20 | 추천 0 | 조회 7099
kaistsoftware 2020.04.20 0 7099
31
4/16 특허 Ideation (이우기/인하대 산업경영공학과)
kaistsoftware | 2020.04.17 | 추천 0 | 조회 8064
kaistsoftware 2020.04.17 0 8064