Color medical image analysis:
<p>Since the early 20th century, medical imaging has been dominated by monochrome imaging modalities such as x-ray, computed tomography, ultrasound, and magnetic resonance imaging. As a result, color information has been overlooked in medical image analysis applications. Recently, various medi...
Gespeichert in:
| Weitere Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Dordrecht [u.a.]
Springer
2013
|
| Schriftenreihe: | Lecture notes in computational vision and biomechanics
6 |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Zusammenfassung: | <p>Since the early 20th century, medical imaging has been dominated by monochrome imaging modalities such as x-ray, computed tomography, ultrasound, and magnetic resonance imaging. As a result, color information has been overlooked in medical image analysis applications. Recently, various medical imaging modalities that involve color information have been introduced. These include cervicography, dermoscopy, fundus photography, gastrointestinal endoscopy, microscopy, and wound photography. However, in comparison to monochrome images, the analysis of color images is a relatively unexplored area. The multivariate nature of color image data presents new challenges for researchers and practitioners as the numerous methods developed for monochrome images are often not directly applicable to multichannel images.</p><p>The goal of this volume is to summarize the state-of-the-art in the utilization of color information in medical image analysis.</p> |
| Beschreibung: | X, 204 S. Ill., graph. Darst. |
| ISBN: | 9789400753884 |
Internformat
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| 245 | 1 | 0 | |a Color medical image analysis |c M. Emre Celebi ..., eds. |
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| 490 | 1 | |a Lecture notes in computational vision and biomechanics |v 6 | |
| 520 | |a <p>Since the early 20th century, medical imaging has been dominated by monochrome imaging modalities such as x-ray, computed tomography, ultrasound, and magnetic resonance imaging. As a result, color information has been overlooked in medical image analysis applications. Recently, various medical imaging modalities that involve color information have been introduced. These include cervicography, dermoscopy, fundus photography, gastrointestinal endoscopy, microscopy, and wound photography. However, in comparison to monochrome images, the analysis of color images is a relatively unexplored area. The multivariate nature of color image data presents new challenges for researchers and practitioners as the numerous methods developed for monochrome images are often not directly applicable to multichannel images.</p><p>The goal of this volume is to summarize the state-of-the-art in the utilization of color information in medical image analysis.</p> | ||
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| 650 | 4 | |a Engineering | |
| 650 | 4 | |a Radiology, Medical | |
| 650 | 4 | |a Computer vision | |
| 650 | 4 | |a Biomedical engineering | |
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Datensatz im Suchindex
| _version_ | 1804150314373218304 |
|---|---|
| adam_text | Contents
A Data Driven Approach to Cervigram Image Analysis and Classification
1
Edward Kim and Xiaolei Huang
Macroscopic
Pigmented
Skin Lesion Segmentation and Its Influence on
Lesion Classification and Diagnosis
................... 15
Pablo G.
Cavalcanti
and Jacob Scharcanski
Color and Spatial Features Integrated Normalized Distance for Density
Based Border Detection in Dermoscopy Images
............ 41
Sinan
Kockara, Mutlu
Mete, and
Sait Suer
A Color
ала
Texture Based Hierarchical K-NN Approach to the
Classification of Non-melanoma Skin Lesions
............. 63
Lucia
Ballerini,
Robert B. Fisher, Ben Aldndge, and Jonathan
Rees
Coíor
Quantization of Dermoscopy Images Using the K-Means
Clustering Algorithm
........................... 87
M. Emre Celebi, Quan Wen, Sae Hwang, and Gerald Schaefer
Grading the Severity of Diabetic
Macular
Edema Cases Based on Color
Eye
Fundus
Images
............................109
Daniel Welfer, Jacob Scharcanski, Pablo
Gautério Cavalcanti,
Diane Ruschel
Marinho,
Laura W-B.
Ludwig, Cleyson
M.
Kitamura,
and Melissa
M.
Dal Pizzol
Colour Image Analysis of Wireless Capsule Endoscopy Video: A Review
129
Mark Fisher and
Michal
Mackiewicz
Automated Prototype Generation for Multi-color Karyotyping
......145
Xuqing Wu, Shishir Shah, and
Fatima
Merchant
Colour Model Analysis for Histopathology Image Processing
.......165
Gloria
Bueno,
Oscar
Déniz, Jesús Salido,
M.
Milagro Fernández,
Noelia
Valiez,
and Marcial García Rojo
χ
Contents
Α
Review
on CAD Tools for Burn Diagnosis
.................181
Aurora
Sáez,
Carmen Serrano, and
Begoña
Acha
Index
......................................203
|
| any_adam_object | 1 |
| author2 | Celebi, M. Emre |
| author2_role | edt |
| author2_variant | m e c me mec |
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| building | Verbundindex |
| bvnumber | BV040991334 |
| classification_rvk | YR 2200 |
| ctrlnum | (OCoLC)854708915 (DE-599)BVBBV040991334 |
| discipline | Medizin |
| format | Book |
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| isbn | 9789400753884 |
| language | English |
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| spelling | Color medical image analysis M. Emre Celebi ..., eds. Dordrecht [u.a.] Springer 2013 X, 204 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Lecture notes in computational vision and biomechanics 6 <p>Since the early 20th century, medical imaging has been dominated by monochrome imaging modalities such as x-ray, computed tomography, ultrasound, and magnetic resonance imaging. As a result, color information has been overlooked in medical image analysis applications. Recently, various medical imaging modalities that involve color information have been introduced. These include cervicography, dermoscopy, fundus photography, gastrointestinal endoscopy, microscopy, and wound photography. However, in comparison to monochrome images, the analysis of color images is a relatively unexplored area. The multivariate nature of color image data presents new challenges for researchers and practitioners as the numerous methods developed for monochrome images are often not directly applicable to multichannel images.</p><p>The goal of this volume is to summarize the state-of-the-art in the utilization of color information in medical image analysis.</p> Ingenieurwissenschaften Engineering Radiology, Medical Computer vision Biomedical engineering Medizin (DE-588)4038243-6 gnd rswk-swf Bildgebendes Verfahren (DE-588)4006617-4 gnd rswk-swf (DE-588)4143413-4 Aufsatzsammlung gnd-content Medizin (DE-588)4038243-6 s Bildgebendes Verfahren (DE-588)4006617-4 s DE-604 Celebi, M. Emre edt Erscheint auch als Online-Ausgabe 978-94-007-5389-1 Lecture notes in computational vision and biomechanics 6 (DE-604)BV040975351 6 Digitalisierung UB Regensburg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025969137&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Color medical image analysis Lecture notes in computational vision and biomechanics Ingenieurwissenschaften Engineering Radiology, Medical Computer vision Biomedical engineering Medizin (DE-588)4038243-6 gnd Bildgebendes Verfahren (DE-588)4006617-4 gnd |
| subject_GND | (DE-588)4038243-6 (DE-588)4006617-4 (DE-588)4143413-4 |
| title | Color medical image analysis |
| title_auth | Color medical image analysis |
| title_exact_search | Color medical image analysis |
| title_full | Color medical image analysis M. Emre Celebi ..., eds. |
| title_fullStr | Color medical image analysis M. Emre Celebi ..., eds. |
| title_full_unstemmed | Color medical image analysis M. Emre Celebi ..., eds. |
| title_short | Color medical image analysis |
| title_sort | color medical image analysis |
| topic | Ingenieurwissenschaften Engineering Radiology, Medical Computer vision Biomedical engineering Medizin (DE-588)4038243-6 gnd Bildgebendes Verfahren (DE-588)4006617-4 gnd |
| topic_facet | Ingenieurwissenschaften Engineering Radiology, Medical Computer vision Biomedical engineering Medizin Bildgebendes Verfahren Aufsatzsammlung |
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| volume_link | (DE-604)BV040975351 |
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