Image segmentation applied to cytology Niels VAN VLIET - PowerPoint PPT Presentation

Image segmentation applied to cytology Niels VAN VLIET <niels@lrde.epita.fr> LRDE seminar, May 14, 2003

Table of contents Table of contents Introduction .......................................................................................... 2 Segmentation ....................................................................................... 17 [1/4] Extraction of the background ............................................................ 18 [2/4] Extraction of the heaps .................................................................... 23 [3/4] Extraction of the nuclei ’s position ...................................................... 27 [4/4] Extraction of the nuclei ’s boundaries ................................................. 30 Conclusion ........................................................................................... 47 Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 1

Introduction Introduction The Automatic Detection of Healthy Or Cancerous Cells ( AD-HOC ) is divided into two parts: • Extraction of the data from the image • Analysis of the data (future work) Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 2

Introduction A few definitions What is a (healthy) cell ? • Nucleus ’ diameter ≈ 10 µ Nucleus • The nucleus ’s boundary is regular Chromatine • The nucleus is round ( � = oval!) Cytoplasm • Nucleus darker than the cytoplasm Background • Cytoplasm darker than the background • Cytoplasm much bigger than the nucleus Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 3

Introduction What is a cancerous cell ? • sizeof ( nucleus ) /sizeof ( cytoplasm ) is big • Nucleus ’ diameter > 13 µ • Dark nucleus • Irregular shape Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 4

Introduction A spot A 2 cm spot magnified 400x: Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 5

Introduction Origin of the images How to create a spot ? • Fine needle aspiration • Chemical destruction of useless objects • Separation of the cells in a bath • Centrifugation • Extraction of the cells sticked on the sides by a centrifuge Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 6

Introduction Problems • Problems of the screening: – Slow – Harmful – Subjective • Solution: Automation – Segmentation – Decision Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 7

Introduction Input Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 8

Introduction Output of the segmentation Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 9

Introduction Problems encountered 9 problems are going to be presented: Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 10

Introduction 1. No color: Normal case 2. Problems of contrast: Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 11

Introduction 3. Fuzzy cells: 4. Different sizes: Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 12

Introduction 5. Heterogeneous surfaces: Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 13

Introduction 6. Heterogeneous shapes: Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 14

Introduction 7. Multiple cells: 8. Heaps: Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 15

Introduction Finding something abnormal We have to accept more than the normal (green) cells, but not to accept other objects (black). Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 16

Segmentation Segmentation Extraction of 1. The background 2. The heaps 3. The position of the nuclei 4. The boundary of the nuclei Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 17

Segmentation [1/4] Extraction of the background [1/4] Extraction of the background Using Watershed[Lezoray 98] Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 18

Segmentation [1/4] Extraction of the background Using Watershed Image Extraction Regions of Markers Watershed Do not work well: • No color • Fuzzy boundaries between cytoplasm and background Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 19

Segmentation [1/4] Extraction of the background [1/4] Using thresholds K-Mean Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 20

Segmentation [1/4] Extraction of the background Threshold using the histogram Problems: • Dust on the light ⇒ Dark points in the background ⇒ Opening • Impurities and heterogeneous cells ⇒ White points in the cells ⇒ Closing Image background Open− Threshold Close Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 21

Segmentation [1/4] Extraction of the background [1/4] Threshold and opening Threshold After the opening Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 22

Segmentation [2/4] Extraction of the heaps [2/4] Extraction of the heaps Separation of the isolated cells and the heaps Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 23

Segmentation [2/4] Extraction of the heaps Heap ’s boundary Heap = Heap + isolated cells stick on the heap Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 24

Segmentation [2/4] Extraction of the heaps Image Threshold Still exist Regions Connected after the Components opening ? Opening Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 25

Segmentation [2/4] Extraction of the heaps [2/4] Original/Threshold/Opening/Result Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 26

Segmentation [3/4] Extraction of the nuclei ’s position [3/4] Extraction of the nuclei ’s position Image Threshold Erosion Last markers Erosion (nucleus) Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 27

Segmentation [3/4] Extraction of the nuclei ’s position [3/4] Original/Threshold + Erosion/Last Erosion Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 28

Segmentation [3/4] Extraction of the nuclei ’s position [3/4] Result Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 29

Segmentation [4/4] Extraction of the nuclei ’s boundaries [4/4] Extraction of the nuclei ’s boundaries Now, the position of the nucleus is known (white cross) The goal is to find the boundary of the nucleus (blue and green line) Watershed Radius Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 30

Segmentation [4/4] Extraction of the nuclei ’s boundaries Using Watershed[Lezoray98] • The markers (where the water comes from) are the position of of the nuclei • The gradient of the image is needed • The ‘water’ should not be stopped by the impurities of the cell Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 31

Segmentation [4/4] Extraction of the nuclei ’s boundaries Beucher ’s Gradient Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 32

Segmentation [4/4] Extraction of the nuclei ’s boundaries Area Closing Clear small dark areas Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 33

Segmentation [4/4] Extraction of the nuclei ’s boundaries Extraction of nuclei ’s boundary using watershed Area Beucher’s Closing Gradient Image Nuclei Watershed Extraction of Markers Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 34

Segmentation [4/4] Extraction of the nuclei ’s boundaries Result Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 35

Segmentation [4/4] Extraction of the nuclei ’s boundaries Over-segmentation Over-segmentation within the nuclei! ⇒ Union of regions that share a boundary ⇒ Many nuclei sticked together share the same region! ⇒ Separation of these regions with distance map Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 36

Segmentation [4/4] Extraction of the nuclei ’s boundaries Separation of interconnected nuclei Last Erosion Mask of Separate Connected Watershed Nuclei Distance Nuclei map Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 37

Segmentation [4/4] Extraction of the nuclei ’s boundaries Do not work well on heterogenous cells. Do not work well on fuzzy cells Image segmentation applied to cytology, Niels VAN VLIET - LRDE seminar, May 14, 2003 38