Berikut beberapa saran untuk penelitian lebih lanjut:
1. Dapat mengembangkan metode pemodelan matematika lainnya dan metode segmentasi bentuk-bentuk image lainnya serta reduksi data yang berkaitan dengan gambar otak dan saraf yang berhubungan dengan kanker otak.
2. Dapat menggunakan metode pemetaan otak lainnya, seperti CT Scan sebagai media untuk pemodelan matematika.
3. Memperbanyak jumlah sampel yang lebih memberikan deskripsi yang lebih akurat.
DAFTAR PUSTAKA
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LAMPIRAN
Lampiran 1. Surat Permohonan Izin Penelitian RSPAD
Lampiran 2. Surat Permohonan Izin Penelitian RSPAD Gatot Soebroto
Lampiran 3. Surat Keterangan Bimbingan Skripsi
Lampiran 4. Pseudo Code High Pass Filter
allocate outputPixelValue[image width] [image height]
allocate window [window width * window height]
edgex := (window width / 2) rounded down edgey := (window height / 2) rounded down
for x from edgex to image width – edgex for y from edgey to image height - edgey
i = 0
for fx from 0 to window width
for fy from 0 to window height
window[i] := inputPixelValue[x+fx-edgex]
[y+fy-edgey]
i := i+1
sort entries in window[]
outputPixelValue[x][y] := window[window width
* window height / 2]
Lampiran 5. Pseudo Code Segmentasi Support Vector Machine 1. a = init_mask
1.1 init_mask = m(90:100,105:135) = 1
1.2 hasil persegi panjang dengan index x= 90-100 dan y = 105-135 bernilai 1
2. phi = buat mask(a)
2.1 phi = bwdist(init_a)-bwdist(1-init_a) + im2double(init_a)-.5;
2.1.1 bwdist = euclidian distant transform untuk warna hitam dan putih dari pixel sekitar.
a. bwdist = sqrt((x1-x2)^2 + (y1-y2)^2)
b. x1 node baris 1, x2 node baris 2, y1, node
kolom 1, y2 node kolom 2.
2.1.2 im2double = convert image jadi angka double.
2.2 looping sebanyak 120 kali
2.2.1 idx = find(phi <= 1.2 & phi >= -1.2
a. idx = index linear dari -1.2 >= phi =<
1.2
2.2.2. cari nilai
a. upts = find(phi<=0); cari linear index kurang dari 0 dari phi
b. vpts = find(phi>0); cari linear index lebih dari 0 dari phi
c. u = mean dari upts
* u = sum(upts)/length(upts) d. v = mean dari vpts
* v = sum(vpts)/length(vpts) 2.2.3 F = (I(idx)-u).^2-(I(idx)-v).^2;
a. F = penyatuan batas nilai 1.2 dengan batas
nilai 0
2.2.4 get_curvature = cari subscript tetangga.
subscript digunakan untuk mencari tumor.
[y x] = ind2sub(size(phi),idx); get subscript
* ind2sub = sigma((((idx - (1 + (idx – 1-(idx-1/idx)))))/idx) + 1)
b. Get subscript tetangga
* ym1 = y-1; xm1=x-1; yp1=y+1; xp1=x+1;