Name
Title | ||
|---|---|---|
A Framework For Morphological Feature Extraction Of Organs From Mr Images For Detection And Classification Of Abnormalities |
Abstract | ||
|---|---|---|
In clinical practice, a misdiagnosis can lead to incorrect or delayed treatment, and in some cases, no treatment at all; consequently, the condition of a patient may worsen to varying degrees, in some cases proving fatal. The accurate 3D reconstruction of organs, which is a pioneering tool of medical image computing (MIC) technology, plays a key role in computer aided diagnosis (CADx), thereby enabling medical professionals to perform enhanced analysis on a region of interest. From here, the shape and structure of the organ coupled with measurements of its volume and curvature can provide significant guidance towards establishing the severity of a disorder or abnormality, consequently supporting improved diagnosis and treatment planning. Moreover, the classification and stratification of organ abnormalities is widely utilised within biomedical, forensic and MIC research for exploring and investigating organ deformations following injury, illness or trauma. This paper presents a tool that calculates, classifies and analyses pancreatic volume and curvature following their 3D reconstruction. Magnetic resonance imaging (MRI) volumes of 115 adult patients are evaluated in order to examine a correlation between these two variables. Such a tool can be utilised in the scope of much greater research and investigation. It can also be incorporated into the development of effective medical image analysis software application in the stratification of subjects and targeting of therapies. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/CBMS.2017.49 | 2017 IEEE 30TH INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS (CBMS) |
Keywords | Field | DocType |
computer aided diagnosis (CADx), organ volume, organ curvature, 3D organ reconstruction, magnetic resonance imaging (MRI) | Computer vision,Radiation treatment planning,Computer-aided diagnosis,Image analysis,Abnormality,Feature extraction,Medical image computing,Artificial intelligence,Radiology,Region of interest,Medicine,3D reconstruction | Conference |
ISSN | Citations | PageRank |
2372-9198 | 1 | 0.37 |
References | Authors | |
1 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Barbara Villarini | 1 | 17 | 4.13 |
| Hykoush Asaturyan | 2 | 1 | 0.37 |
| E. Louise Thomas | 3 | 1 | 1.04 |
| Rhys Mould | 4 | 1 | 0.37 |
| Jimmy D Bell | 5 | 4 | 2.34 |