SISTEM ZA ANALIZU MAMOGRAFIJE DOJKE POMOĆU RAČUNARA
Ključne reči:
analiza slike, mašinskog učenje
Apstrakt
Cilj ovog rada ogleda u razvoju grafičkog-korisničkog interfejsa (engl. Graphical User Interface – GUI), baziranog na algoritmima iz tradicionalne računarske vizije , koji će potencijalno olakšati intelektualni napor i redukovati utrošeno vreme radiologa prilikom analize i intereptacije mamografije dojke u kliničkoj praksi.
Reference
[1] Rafael Gonzalez: Digital Image Processing
[2] Adaptive Histogram Equalization – Wikipedia
[3] Efficient Contrast Enhancement using Adaptive Gamma Correction and Cumulative Intensity Distribution
[4] Y. Kim, Contrast enhancement using brightness preserving bi-histogram equalization
[5] Y. Wan, Q. Chen, and B. Zhang, Image enhancement based on equal area dualistic sub-image histogram equalization method
[6] K. S. Sim, C. P. Tso, and Y. Tan, Recursive sub-image histogram equalization applied to gray-scale images
[7] M. Kim and M. G. Chung, Recursively separated and weighted histogram equalization for brightness preservation and contrast enhancement
[2] Adaptive Histogram Equalization – Wikipedia
[3] Efficient Contrast Enhancement using Adaptive Gamma Correction and Cumulative Intensity Distribution
[4] Y. Kim, Contrast enhancement using brightness preserving bi-histogram equalization
[5] Y. Wan, Q. Chen, and B. Zhang, Image enhancement based on equal area dualistic sub-image histogram equalization method
[6] K. S. Sim, C. P. Tso, and Y. Tan, Recursive sub-image histogram equalization applied to gray-scale images
[7] M. Kim and M. G. Chung, Recursively separated and weighted histogram equalization for brightness preservation and contrast enhancement
Objavljeno
2021-11-06
Sekcija
Elektrotehničko i računarsko inženjerstvo
